2022-02-10 16:43:57 +01:00
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2005-04-16 15:20:36 -07:00
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random: use BLAKE2s instead of SHA1 in extraction
This commit addresses one of the lower hanging fruits of the RNG: its
usage of SHA1.
BLAKE2s is generally faster, and certainly more secure, than SHA1, which
has [1] been [2] really [3] very [4] broken [5]. Additionally, the
current construction in the RNG doesn't use the full SHA1 function, as
specified, and allows overwriting the IV with RDRAND output in an
undocumented way, even in the case when RDRAND isn't set to "trusted",
which means potential malicious IV choices. And its short length means
that keeping only half of it secret when feeding back into the mixer
gives us only 2^80 bits of forward secrecy. In other words, not only is
the choice of hash function dated, but the use of it isn't really great
either.
This commit aims to fix both of these issues while also keeping the
general structure and semantics as close to the original as possible.
Specifically:
a) Rather than overwriting the hash IV with RDRAND, we put it into
BLAKE2's documented "salt" and "personal" fields, which were
specifically created for this type of usage.
b) Since this function feeds the full hash result back into the
entropy collector, we only return from it half the length of the
hash, just as it was done before. This increases the
construction's forward secrecy from 2^80 to a much more
comfortable 2^128.
c) Rather than using the raw "sha1_transform" function alone, we
instead use the full proper BLAKE2s function, with finalization.
This also has the advantage of supplying 16 bytes at a time rather than
SHA1's 10 bytes, which, in addition to having a faster compression
function to begin with, means faster extraction in general. On an Intel
i7-11850H, this commit makes initial seeding around 131% faster.
BLAKE2s itself has the nice property of internally being based on the
ChaCha permutation, which the RNG is already using for expansion, so
there shouldn't be any issue with newness, funkiness, or surprising CPU
behavior, since it's based on something already in use.
[1] https://eprint.iacr.org/2005/010.pdf
[2] https://www.iacr.org/archive/crypto2005/36210017/36210017.pdf
[3] https://eprint.iacr.org/2015/967.pdf
[4] https://shattered.io/static/shattered.pdf
[5] https://www.usenix.org/system/files/sec20-leurent.pdf
Reviewed-by: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Reviewed-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2021-12-21 16:31:27 +01:00
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2005-04-16 15:25:56 -07:00
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2022-02-11 12:29:33 +01:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2005-04-16 15:20:36 -07:00
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2019-06-07 14:25:15 -04:00
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2005-04-16 15:20:36 -07:00
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2022-01-24 10:39:13 +01:00
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2005-04-16 15:20:36 -07:00
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2008-07-23 21:28:13 -07:00
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2016-07-31 00:23:08 +10:00
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2005-04-16 15:20:36 -07:00
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2014-06-14 23:38:36 -04:00
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2005-04-16 15:20:36 -07:00
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2012-07-02 07:52:16 -04:00
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2013-10-03 01:08:15 -04:00
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2013-08-30 09:39:53 +02:00
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2018-04-25 01:12:32 -04:00
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random: introduce getrandom(2) system call
The getrandom(2) system call was requested by the LibreSSL Portable
developers. It is analoguous to the getentropy(2) system call in
OpenBSD.
The rationale of this system call is to provide resiliance against
file descriptor exhaustion attacks, where the attacker consumes all
available file descriptors, forcing the use of the fallback code where
/dev/[u]random is not available. Since the fallback code is often not
well-tested, it is better to eliminate this potential failure mode
entirely.
The other feature provided by this new system call is the ability to
request randomness from the /dev/urandom entropy pool, but to block
until at least 128 bits of entropy has been accumulated in the
/dev/urandom entropy pool. Historically, the emphasis in the
/dev/urandom development has been to ensure that urandom pool is
initialized as quickly as possible after system boot, and preferably
before the init scripts start execution.
This is because changing /dev/urandom reads to block represents an
interface change that could potentially break userspace which is not
acceptable. In practice, on most x86 desktop and server systems, in
general the entropy pool can be initialized before it is needed (and
in modern kernels, we will printk a warning message if not). However,
on an embedded system, this may not be the case. And so with this new
interface, we can provide the functionality of blocking until the
urandom pool has been initialized. Any userspace program which uses
this new functionality must take care to assure that if it is used
during the boot process, that it will not cause the init scripts or
other portions of the system startup to hang indefinitely.
SYNOPSIS
#include <linux/random.h>
int getrandom(void *buf, size_t buflen, unsigned int flags);
DESCRIPTION
The system call getrandom() fills the buffer pointed to by buf
with up to buflen random bytes which can be used to seed user
space random number generators (i.e., DRBG's) or for other
cryptographic uses. It should not be used for Monte Carlo
simulations or other programs/algorithms which are doing
probabilistic sampling.
If the GRND_RANDOM flags bit is set, then draw from the
/dev/random pool instead of the /dev/urandom pool. The
/dev/random pool is limited based on the entropy that can be
obtained from environmental noise, so if there is insufficient
entropy, the requested number of bytes may not be returned.
If there is no entropy available at all, getrandom(2) will
either block, or return an error with errno set to EAGAIN if
the GRND_NONBLOCK bit is set in flags.
If the GRND_RANDOM bit is not set, then the /dev/urandom pool
will be used. Unlike using read(2) to fetch data from
/dev/urandom, if the urandom pool has not been sufficiently
initialized, getrandom(2) will block (or return -1 with the
errno set to EAGAIN if the GRND_NONBLOCK bit is set in flags).
The getentropy(2) system call in OpenBSD can be emulated using
the following function:
int getentropy(void *buf, size_t buflen)
{
int ret;
if (buflen > 256)
goto failure;
ret = getrandom(buf, buflen, 0);
if (ret < 0)
return ret;
if (ret == buflen)
return 0;
failure:
errno = EIO;
return -1;
}
RETURN VALUE
On success, the number of bytes that was filled in the buf is
returned. This may not be all the bytes requested by the
caller via buflen if insufficient entropy was present in the
/dev/random pool, or if the system call was interrupted by a
signal.
On error, -1 is returned, and errno is set appropriately.
ERRORS
EINVAL An invalid flag was passed to getrandom(2)
EFAULT buf is outside the accessible address space.
EAGAIN The requested entropy was not available, and
getentropy(2) would have blocked if the
GRND_NONBLOCK flag was not set.
EINTR While blocked waiting for entropy, the call was
interrupted by a signal handler; see the description
of how interrupted read(2) calls on "slow" devices
are handled with and without the SA_RESTART flag
in the signal(7) man page.
NOTES
For small requests (buflen <= 256) getrandom(2) will not
return EINTR when reading from the urandom pool once the
entropy pool has been initialized, and it will return all of
the bytes that have been requested. This is the recommended
way to use getrandom(2), and is designed for compatibility
with OpenBSD's getentropy() system call.
However, if you are using GRND_RANDOM, then getrandom(2) may
block until the entropy accounting determines that sufficient
environmental noise has been gathered such that getrandom(2)
will be operating as a NRBG instead of a DRBG for those people
who are working in the NIST SP 800-90 regime. Since it may
block for a long time, these guarantees do *not* apply. The
user may want to interrupt a hanging process using a signal,
so blocking until all of the requested bytes are returned
would be unfriendly.
For this reason, the user of getrandom(2) MUST always check
the return value, in case it returns some error, or if fewer
bytes than requested was returned. In the case of
!GRND_RANDOM and small request, the latter should never
happen, but the careful userspace code (and all crypto code
should be careful) should check for this anyway!
Finally, unless you are doing long-term key generation (and
perhaps not even then), you probably shouldn't be using
GRND_RANDOM. The cryptographic algorithms used for
/dev/urandom are quite conservative, and so should be
sufficient for all purposes. The disadvantage of GRND_RANDOM
is that it can block, and the increased complexity required to
deal with partially fulfilled getrandom(2) requests.
Signed-off-by: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Zach Brown <zab@zabbo.net>
2014-07-17 04:13:05 -04:00
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2016-05-20 17:01:00 -07:00
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2022-02-11 13:41:41 +01:00
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2022-05-01 13:51:34 +02:00
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2022-05-07 14:03:46 +02:00
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2022-10-01 01:10:50 +02:00
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2018-11-16 17:26:21 -08:00
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random: use BLAKE2s instead of SHA1 in extraction
This commit addresses one of the lower hanging fruits of the RNG: its
usage of SHA1.
BLAKE2s is generally faster, and certainly more secure, than SHA1, which
has [1] been [2] really [3] very [4] broken [5]. Additionally, the
current construction in the RNG doesn't use the full SHA1 function, as
specified, and allows overwriting the IV with RDRAND output in an
undocumented way, even in the case when RDRAND isn't set to "trusted",
which means potential malicious IV choices. And its short length means
that keeping only half of it secret when feeding back into the mixer
gives us only 2^80 bits of forward secrecy. In other words, not only is
the choice of hash function dated, but the use of it isn't really great
either.
This commit aims to fix both of these issues while also keeping the
general structure and semantics as close to the original as possible.
Specifically:
a) Rather than overwriting the hash IV with RDRAND, we put it into
BLAKE2's documented "salt" and "personal" fields, which were
specifically created for this type of usage.
b) Since this function feeds the full hash result back into the
entropy collector, we only return from it half the length of the
hash, just as it was done before. This increases the
construction's forward secrecy from 2^80 to a much more
comfortable 2^128.
c) Rather than using the raw "sha1_transform" function alone, we
instead use the full proper BLAKE2s function, with finalization.
This also has the advantage of supplying 16 bytes at a time rather than
SHA1's 10 bytes, which, in addition to having a faster compression
function to begin with, means faster extraction in general. On an Intel
i7-11850H, this commit makes initial seeding around 131% faster.
BLAKE2s itself has the nice property of internally being based on the
ChaCha permutation, which the RNG is already using for expansion, so
there shouldn't be any issue with newness, funkiness, or surprising CPU
behavior, since it's based on something already in use.
[1] https://eprint.iacr.org/2005/010.pdf
[2] https://www.iacr.org/archive/crypto2005/36210017/36210017.pdf
[3] https://eprint.iacr.org/2015/967.pdf
[4] https://shattered.io/static/shattered.pdf
[5] https://www.usenix.org/system/files/sec20-leurent.pdf
Reviewed-by: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Reviewed-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2021-12-21 16:31:27 +01:00
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2022-10-29 01:42:02 +02:00
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2005-04-16 15:20:36 -07:00
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2012-07-02 07:52:16 -04:00
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2005-04-16 15:20:36 -07:00
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2022-02-11 12:53:34 +01:00
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2015-06-09 18:19:39 +08:00
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2016-06-12 18:13:36 -04:00
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2022-02-11 12:53:34 +01:00
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2022-05-08 13:20:30 +02:00
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2016-06-12 18:13:36 -04:00
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2022-05-08 13:20:30 +02:00
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random: use static branch for crng_ready()
Since crng_ready() is only false briefly during initialization and then
forever after becomes true, we don't need to evaluate it after, making
it a prime candidate for a static branch.
One complication, however, is that it changes state in a particular call
to credit_init_bits(), which might be made from atomic context, which
means we must kick off a workqueue to change the static key. Further
complicating things, credit_init_bits() may be called sufficiently early
on in system initialization such that system_wq is NULL.
Fortunately, there exists the nice function execute_in_process_context(),
which will immediately execute the function if !in_interrupt(), and
otherwise defer it to a workqueue. During early init, before workqueues
are available, in_interrupt() is always false, because interrupts
haven't even been enabled yet, which means the function in that case
executes immediately. Later on, after workqueues are available,
in_interrupt() might be true, but in that case, the work is queued in
system_wq and all goes well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-03 15:30:45 +02:00
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2022-05-08 13:20:30 +02:00
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2022-02-11 12:53:34 +01:00
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2022-11-16 17:16:37 +01:00
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2016-06-12 18:13:36 -04:00
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2022-02-11 12:53:34 +01:00
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2022-03-22 09:17:20 -07:00
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random: quiet urandom warning ratelimit suppression message
random.c ratelimits how much it warns about uninitialized urandom reads
using __ratelimit(). When the RNG is finally initialized, it prints the
number of missed messages due to ratelimiting.
It has been this way since that functionality was introduced back in
2018. Recently, cc1e127bfa95 ("random: remove ratelimiting for in-kernel
unseeded randomness") put a bit more stress on the urandom ratelimiting,
which teased out a bug in the implementation.
Specifically, when under pressure, __ratelimit() will print its own
message and reset the count back to 0, making the final message at the
end less useful. Secondly, it does so as a pr_warn(), which apparently
is undesirable for people's CI.
Fortunately, __ratelimit() has the RATELIMIT_MSG_ON_RELEASE flag exactly
for this purpose, so we set the flag.
Fixes: 4e00b339e264 ("random: rate limit unseeded randomness warnings")
Cc: stable@vger.kernel.org
Reported-by: Jon Hunter <jonathanh@nvidia.com>
Reported-by: Ron Economos <re@w6rz.net>
Tested-by: Ron Economos <re@w6rz.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-06-16 15:00:51 +02:00
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random: remove ratelimiting for in-kernel unseeded randomness
The CONFIG_WARN_ALL_UNSEEDED_RANDOM debug option controls whether the
kernel warns about all unseeded randomness or just the first instance.
There's some complicated rate limiting and comparison to the previous
caller, such that even with CONFIG_WARN_ALL_UNSEEDED_RANDOM enabled,
developers still don't see all the messages or even an accurate count of
how many were missed. This is the result of basically parallel
mechanisms aimed at accomplishing more or less the same thing, added at
different points in random.c history, which sort of compete with the
first-instance-only limiting we have now.
It turns out, however, that nobody cares about the first unseeded
randomness instance of in-kernel users. The same first user has been
there for ages now, and nobody is doing anything about it. It isn't even
clear that anybody _can_ do anything about it. Most places that can do
something about it have switched over to using get_random_bytes_wait()
or wait_for_random_bytes(), which is the right thing to do, but there is
still much code that needs randomness sometimes during init, and as a
geeneral rule, if you're not using one of the _wait functions or the
readiness notifier callback, you're bound to be doing it wrong just
based on that fact alone.
So warning about this same first user that can't easily change is simply
not an effective mechanism for anything at all. Users can't do anything
about it, as the Kconfig text points out -- the problem isn't in
userspace code -- and kernel developers don't or more often can't react
to it.
Instead, show the warning for all instances when CONFIG_WARN_ALL_UNSEEDED_RANDOM
is set, so that developers can debug things need be, or if it isn't set,
don't show a warning at all.
At the same time, CONFIG_WARN_ALL_UNSEEDED_RANDOM now implies setting
random.ratelimit_disable=1 on by default, since if you care about one
you probably care about the other too. And we can clean up usage around
the related urandom_warning ratelimiter as well (whose behavior isn't
changing), so that it properly counts missed messages after the 10
message threshold is reached.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-09 16:13:18 +02:00
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2018-04-25 01:12:32 -04:00
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2022-02-11 12:53:34 +01:00
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2022-03-22 09:17:20 -07:00
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2022-10-05 12:54:38 +02:00
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2022-10-05 17:50:20 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 16:17:12 +02:00
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random: use static branch for crng_ready()
Since crng_ready() is only false briefly during initialization and then
forever after becomes true, we don't need to evaluate it after, making
it a prime candidate for a static branch.
One complication, however, is that it changes state in a particular call
to credit_init_bits(), which might be made from atomic context, which
means we must kick off a workqueue to change the static key. Further
complicating things, credit_init_bits() may be called sufficiently early
on in system initialization such that system_wq is NULL.
Fortunately, there exists the nice function execute_in_process_context(),
which will immediately execute the function if !in_interrupt(), and
otherwise defer it to a workqueue. During early init, before workqueues
are available, in_interrupt() is always false, because interrupts
haven't even been enabled yet, which means the function in that case
executes immediately. Later on, after workqueues are available,
in_interrupt() might be true, but in that case, the work is queued in
system_wq and all goes well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-03 15:30:45 +02:00
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2022-02-11 12:53:34 +01:00
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2022-03-22 09:17:20 -07:00
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2022-10-05 12:54:38 +02:00
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2022-11-01 20:08:32 +01:00
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2022-10-05 12:54:38 +02:00
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2022-02-11 12:53:34 +01:00
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2022-03-08 11:20:17 -07:00
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2022-02-11 12:53:34 +01:00
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random: check for signal and try earlier when generating entropy
Rather than waiting a full second in an interruptable waiter before
trying to generate entropy, try to generate entropy first and wait
second. While waiting one second might give an extra second for getting
entropy from elsewhere, we're already pretty late in the init process
here, and whatever else is generating entropy will still continue to
contribute. This has implications on signal handling: we call
try_to_generate_entropy() from wait_for_random_bytes(), and
wait_for_random_bytes() always uses wait_event_interruptible_timeout()
when waiting, since it's called by userspace code in restartable
contexts, where signals can pend. Since try_to_generate_entropy() now
runs first, if a signal is pending, it's necessary for
try_to_generate_entropy() to check for signals, since it won't hit the
wait until after try_to_generate_entropy() has returned. And even before
this change, when entering a busy loop in try_to_generate_entropy(), we
should have been checking to see if any signals are pending, so that a
process doesn't get stuck in that loop longer than expected.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-08 10:12:16 -07:00
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2022-02-11 12:53:34 +01:00
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2022-03-08 11:20:17 -07:00
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2022-02-11 12:53:34 +01:00
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2022-11-16 17:16:37 +01:00
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random: remove ratelimiting for in-kernel unseeded randomness
The CONFIG_WARN_ALL_UNSEEDED_RANDOM debug option controls whether the
kernel warns about all unseeded randomness or just the first instance.
There's some complicated rate limiting and comparison to the previous
caller, such that even with CONFIG_WARN_ALL_UNSEEDED_RANDOM enabled,
developers still don't see all the messages or even an accurate count of
how many were missed. This is the result of basically parallel
mechanisms aimed at accomplishing more or less the same thing, added at
different points in random.c history, which sort of compete with the
first-instance-only limiting we have now.
It turns out, however, that nobody cares about the first unseeded
randomness instance of in-kernel users. The same first user has been
there for ages now, and nobody is doing anything about it. It isn't even
clear that anybody _can_ do anything about it. Most places that can do
something about it have switched over to using get_random_bytes_wait()
or wait_for_random_bytes(), which is the right thing to do, but there is
still much code that needs randomness sometimes during init, and as a
geeneral rule, if you're not using one of the _wait functions or the
readiness notifier callback, you're bound to be doing it wrong just
based on that fact alone.
So warning about this same first user that can't easily change is simply
not an effective mechanism for anything at all. Users can't do anything
about it, as the Kconfig text points out -- the problem isn't in
userspace code -- and kernel developers don't or more often can't react
to it.
Instead, show the warning for all instances when CONFIG_WARN_ALL_UNSEEDED_RANDOM
is set, so that developers can debug things need be, or if it isn't set,
don't show a warning at all.
At the same time, CONFIG_WARN_ALL_UNSEEDED_RANDOM now implies setting
random.ratelimit_disable=1 on by default, since if you care about one
you probably care about the other too. And we can clean up usage around
the related urandom_warning ratelimiter as well (whose behavior isn't
changing), so that it properly counts missed messages after the 10
message threshold is reached.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-09 16:13:18 +02:00
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2022-05-13 16:17:12 +02:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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2005-04-16 15:20:36 -07:00
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2022-02-11 12:53:34 +01:00
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2005-04-16 15:20:36 -07:00
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2022-02-11 12:53:34 +01:00
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2016-06-12 18:13:36 -04:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-10-05 12:54:38 +02:00
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2022-02-11 12:53:34 +01:00
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random: use rejection sampling for uniform bounded random integers
Until the very recent commits, many bounded random integers were
calculated using `get_random_u32() % max_plus_one`, which not only
incurs the price of a division -- indicating performance mostly was not
a real issue -- but also does not result in a uniformly distributed
output if max_plus_one is not a power of two. Recent commits moved to
using `prandom_u32_max(max_plus_one)`, which replaces the division with
a faster multiplication, but still does not solve the issue with
non-uniform output.
For some users, maybe this isn't a problem, and for others, maybe it is,
but for the majority of users, probably the question has never been
posed and analyzed, and nobody thought much about it, probably assuming
random is random is random. In other words, the unthinking expectation
of most users is likely that the resultant numbers are uniform.
So we implement here an efficient way of generating uniform bounded
random integers. Through use of compile-time evaluation, and avoiding
divisions as much as possible, this commit introduces no measurable
overhead. At least for hot-path uses tested, any potential difference
was lost in the noise. On both clang and gcc, code generation is pretty
small.
The new function, get_random_u32_below(), lives in random.h, rather than
prandom.h, and has a "get_random_xxx" function name, because it is
suitable for all uses, including cryptography.
In order to be efficient, we implement a kernel-specific variant of
Daniel Lemire's algorithm from "Fast Random Integer Generation in an
Interval", linked below. The kernel's variant takes advantage of
constant folding to avoid divisions entirely in the vast majority of
cases, works on both 32-bit and 64-bit architectures, and requests a
minimal amount of bytes from the RNG.
Link: https://arxiv.org/pdf/1805.10941.pdf
Cc: stable@vger.kernel.org # to ease future backports that use this api
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-10-08 20:42:54 -06:00
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2022-10-19 23:19:35 -06:00
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2022-02-11 12:53:34 +01:00
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2022-03-22 09:17:20 -07:00
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2022-10-05 17:50:20 +02:00
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2016-06-12 18:13:36 -04:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2016-06-12 18:13:36 -04:00
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2022-11-17 17:47:12 +01:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2022-05-13 13:18:46 +02:00
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2016-06-12 18:13:36 -04:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2022-11-17 17:47:12 +01:00
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2016-06-12 18:13:36 -04:00
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2022-11-17 17:47:12 +01:00
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2022-01-15 14:57:22 +01:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2016-06-12 18:13:36 -04:00
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2022-11-17 17:47:12 +01:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2022-02-06 23:51:41 +01:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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random: use static branch for crng_ready()
Since crng_ready() is only false briefly during initialization and then
forever after becomes true, we don't need to evaluate it after, making
it a prime candidate for a static branch.
One complication, however, is that it changes state in a particular call
to credit_init_bits(), which might be made from atomic context, which
means we must kick off a workqueue to change the static key. Further
complicating things, credit_init_bits() may be called sufficiently early
on in system initialization such that system_wq is NULL.
Fortunately, there exists the nice function execute_in_process_context(),
which will immediately execute the function if !in_interrupt(), and
otherwise defer it to a workqueue. During early init, before workqueues
are available, in_interrupt() is always false, because interrupts
haven't even been enabled yet, which means the function in that case
executes immediately. Later on, after workqueues are available,
in_interrupt() might be true, but in that case, the work is queued in
system_wq and all goes well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-03 15:30:45 +02:00
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2022-05-08 13:20:30 +02:00
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2022-02-09 19:57:06 +01:00
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2016-06-12 18:13:36 -04:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2022-02-11 12:53:34 +01:00
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2022-07-30 01:12:25 +02:00
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2022-02-11 12:53:34 +01:00
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2022-04-18 20:57:31 +02:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2016-06-12 18:13:36 -04:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2021-12-20 16:41:57 -06:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2022-04-18 20:57:31 +02:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2016-05-02 02:04:41 -04:00
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2016-05-04 13:29:18 -04:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2016-05-04 13:29:18 -04:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2016-05-04 13:29:18 -04:00
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2022-01-15 14:57:22 +01:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2016-05-04 13:29:18 -04:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
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2022-05-08 13:20:30 +02:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2022-03-08 11:20:17 -07:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
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2022-05-08 13:20:30 +02:00
|
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random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
|
|
|
random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
|
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|
random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
|
|
|
random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2016-05-04 13:29:18 -04:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2016-05-04 13:29:18 -04:00
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2022-05-13 13:18:46 +02:00
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2016-06-12 18:13:36 -04:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-11-04 12:47:43 +01:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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random: remove ratelimiting for in-kernel unseeded randomness
The CONFIG_WARN_ALL_UNSEEDED_RANDOM debug option controls whether the
kernel warns about all unseeded randomness or just the first instance.
There's some complicated rate limiting and comparison to the previous
caller, such that even with CONFIG_WARN_ALL_UNSEEDED_RANDOM enabled,
developers still don't see all the messages or even an accurate count of
how many were missed. This is the result of basically parallel
mechanisms aimed at accomplishing more or less the same thing, added at
different points in random.c history, which sort of compete with the
first-instance-only limiting we have now.
It turns out, however, that nobody cares about the first unseeded
randomness instance of in-kernel users. The same first user has been
there for ages now, and nobody is doing anything about it. It isn't even
clear that anybody _can_ do anything about it. Most places that can do
something about it have switched over to using get_random_bytes_wait()
or wait_for_random_bytes(), which is the right thing to do, but there is
still much code that needs randomness sometimes during init, and as a
geeneral rule, if you're not using one of the _wait functions or the
readiness notifier callback, you're bound to be doing it wrong just
based on that fact alone.
So warning about this same first user that can't easily change is simply
not an effective mechanism for anything at all. Users can't do anything
about it, as the Kconfig text points out -- the problem isn't in
userspace code -- and kernel developers don't or more often can't react
to it.
Instead, show the warning for all instances when CONFIG_WARN_ALL_UNSEEDED_RANDOM
is set, so that developers can debug things need be, or if it isn't set,
don't show a warning at all.
At the same time, CONFIG_WARN_ALL_UNSEEDED_RANDOM now implies setting
random.ratelimit_disable=1 on by default, since if you care about one
you probably care about the other too. And we can clean up usage around
the related urandom_warning ratelimiter as well (whose behavior isn't
changing), so that it properly counts missed messages after the 10
message threshold is reached.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-09 16:13:18 +02:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-19 17:31:36 -06:00
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2022-02-11 12:53:34 +01:00
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2022-05-19 17:31:36 -06:00
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2022-02-11 12:53:34 +01:00
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2022-05-19 17:31:36 -06:00
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2022-02-11 12:53:34 +01:00
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random: do not allow user to keep crng key around on stack
The fast key erasure RNG design relies on the key that's used to be used
and then discarded. We do this, making judicious use of
memzero_explicit(). However, reads to /dev/urandom and calls to
getrandom() involve a copy_to_user(), and userspace can use FUSE or
userfaultfd, or make a massive call, dynamically remap memory addresses
as it goes, and set the process priority to idle, in order to keep a
kernel stack alive indefinitely. By probing
/proc/sys/kernel/random/entropy_avail to learn when the crng key is
refreshed, a malicious userspace could mount this attack every 5 minutes
thereafter, breaking the crng's forward secrecy.
In order to fix this, we just overwrite the stack's key with the first
32 bytes of the "free" fast key erasure output. If we're returning <= 32
bytes to the user, then we can still return those bytes directly, so
that short reads don't become slower. And for long reads, the difference
is hopefully lost in the amortization, so it doesn't change much, with
that amortization helping variously for medium reads.
We don't need to do this for get_random_bytes() and the various
kernel-space callers, and later, if we ever switch to always batching,
this won't be necessary either, so there's no need to change the API of
these functions.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Jann Horn <jannh@google.com>
Fixes: c92e040d575a ("random: add backtracking protection to the CRNG")
Fixes: 186873c549df ("random: use simpler fast key erasure flow on per-cpu keys")
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-05 16:40:51 +02:00
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2022-06-20 11:03:48 +02:00
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random: do not allow user to keep crng key around on stack
The fast key erasure RNG design relies on the key that's used to be used
and then discarded. We do this, making judicious use of
memzero_explicit(). However, reads to /dev/urandom and calls to
getrandom() involve a copy_to_user(), and userspace can use FUSE or
userfaultfd, or make a massive call, dynamically remap memory addresses
as it goes, and set the process priority to idle, in order to keep a
kernel stack alive indefinitely. By probing
/proc/sys/kernel/random/entropy_avail to learn when the crng key is
refreshed, a malicious userspace could mount this attack every 5 minutes
thereafter, breaking the crng's forward secrecy.
In order to fix this, we just overwrite the stack's key with the first
32 bytes of the "free" fast key erasure output. If we're returning <= 32
bytes to the user, then we can still return those bytes directly, so
that short reads don't become slower. And for long reads, the difference
is hopefully lost in the amortization, so it doesn't change much, with
that amortization helping variously for medium reads.
We don't need to do this for get_random_bytes() and the various
kernel-space callers, and later, if we ever switch to always batching,
this won't be necessary either, so there's no need to change the API of
these functions.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Jann Horn <jannh@google.com>
Fixes: c92e040d575a ("random: add backtracking protection to the CRNG")
Fixes: 186873c549df ("random: use simpler fast key erasure flow on per-cpu keys")
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-05 16:40:51 +02:00
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2022-05-19 17:31:36 -06:00
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random: do not allow user to keep crng key around on stack
The fast key erasure RNG design relies on the key that's used to be used
and then discarded. We do this, making judicious use of
memzero_explicit(). However, reads to /dev/urandom and calls to
getrandom() involve a copy_to_user(), and userspace can use FUSE or
userfaultfd, or make a massive call, dynamically remap memory addresses
as it goes, and set the process priority to idle, in order to keep a
kernel stack alive indefinitely. By probing
/proc/sys/kernel/random/entropy_avail to learn when the crng key is
refreshed, a malicious userspace could mount this attack every 5 minutes
thereafter, breaking the crng's forward secrecy.
In order to fix this, we just overwrite the stack's key with the first
32 bytes of the "free" fast key erasure output. If we're returning <= 32
bytes to the user, then we can still return those bytes directly, so
that short reads don't become slower. And for long reads, the difference
is hopefully lost in the amortization, so it doesn't change much, with
that amortization helping variously for medium reads.
We don't need to do this for get_random_bytes() and the various
kernel-space callers, and later, if we ever switch to always batching,
this won't be necessary either, so there's no need to change the API of
these functions.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Jann Horn <jannh@google.com>
Fixes: c92e040d575a ("random: add backtracking protection to the CRNG")
Fixes: 186873c549df ("random: use simpler fast key erasure flow on per-cpu keys")
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-05 16:40:51 +02:00
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2022-02-11 12:53:34 +01:00
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random: allow partial reads if later user copies fail
Rather than failing entirely if a copy_to_user() fails at some point,
instead we should return a partial read for the amount that succeeded
prior, unless none succeeded at all, in which case we return -EFAULT as
before.
This makes it consistent with other reader interfaces. For example, the
following snippet for /dev/zero outputs "4" followed by "1":
int fd;
void *x = mmap(NULL, 4096, PROT_WRITE, MAP_ANONYMOUS | MAP_PRIVATE, -1, 0);
assert(x != MAP_FAILED);
fd = open("/dev/zero", O_RDONLY);
assert(fd >= 0);
printf("%zd\n", read(fd, x, 4));
printf("%zd\n", read(fd, x + 4095, 4));
close(fd);
This brings that same standard behavior to the various RNG reader
interfaces.
While we're at it, we can streamline the loop logic a little bit.
Suggested-by: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Jann Horn <jannh@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-07 21:23:08 +02:00
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2022-05-19 17:31:36 -06:00
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2022-02-11 12:53:34 +01:00
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2022-05-19 17:31:36 -06:00
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random: allow partial reads if later user copies fail
Rather than failing entirely if a copy_to_user() fails at some point,
instead we should return a partial read for the amount that succeeded
prior, unless none succeeded at all, in which case we return -EFAULT as
before.
This makes it consistent with other reader interfaces. For example, the
following snippet for /dev/zero outputs "4" followed by "1":
int fd;
void *x = mmap(NULL, 4096, PROT_WRITE, MAP_ANONYMOUS | MAP_PRIVATE, -1, 0);
assert(x != MAP_FAILED);
fd = open("/dev/zero", O_RDONLY);
assert(fd >= 0);
printf("%zd\n", read(fd, x, 4));
printf("%zd\n", read(fd, x + 4095, 4));
close(fd);
This brings that same standard behavior to the various RNG reader
interfaces.
While we're at it, we can streamline the loop logic a little bit.
Suggested-by: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Jann Horn <jannh@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-07 21:23:08 +02:00
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random: check for signals every PAGE_SIZE chunk of /dev/[u]random
In 1448769c9cdb ("random: check for signal_pending() outside of
need_resched() check"), Jann pointed out that we previously were only
checking the TIF_NOTIFY_SIGNAL and TIF_SIGPENDING flags if the process
had TIF_NEED_RESCHED set, which meant in practice, super long reads to
/dev/[u]random would delay signal handling by a long time. I tried this
using the below program, and indeed I wasn't able to interrupt a
/dev/urandom read until after several megabytes had been read. The bug
he fixed has always been there, and so code that reads from /dev/urandom
without checking the return value of read() has mostly worked for a long
time, for most sizes, not just for <= 256.
Maybe it makes sense to keep that code working. The reason it was so
small prior, ignoring the fact that it didn't work anyway, was likely
because /dev/random used to block, and that could happen for pretty
large lengths of time while entropy was gathered. But now, it's just a
chacha20 call, which is extremely fast and is just operating on pure
data, without having to wait for some external event. In that sense,
/dev/[u]random is a lot more like /dev/zero.
Taking a page out of /dev/zero's read_zero() function, it always returns
at least one chunk, and then checks for signals after each chunk. Chunk
sizes there are of length PAGE_SIZE. Let's just copy the same thing for
/dev/[u]random, and check for signals and cond_resched() for every
PAGE_SIZE amount of data. This makes the behavior more consistent with
expectations, and should mitigate the impact of Jann's fix for the
age-old signal check bug.
---- test program ----
#include <unistd.h>
#include <signal.h>
#include <stdio.h>
#include <sys/random.h>
static unsigned char x[~0U];
static void handle(int) { }
int main(int argc, char *argv[])
{
pid_t pid = getpid(), child;
signal(SIGUSR1, handle);
if (!(child = fork())) {
for (;;)
kill(pid, SIGUSR1);
}
pause();
printf("interrupted after reading %zd bytes\n", getrandom(x, sizeof(x), 0));
kill(child, SIGTERM);
return 0;
}
Cc: Jann Horn <jannh@google.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-06 02:36:16 +02:00
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2022-05-19 17:31:36 -06:00
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random: allow partial reads if later user copies fail
Rather than failing entirely if a copy_to_user() fails at some point,
instead we should return a partial read for the amount that succeeded
prior, unless none succeeded at all, in which case we return -EFAULT as
before.
This makes it consistent with other reader interfaces. For example, the
following snippet for /dev/zero outputs "4" followed by "1":
int fd;
void *x = mmap(NULL, 4096, PROT_WRITE, MAP_ANONYMOUS | MAP_PRIVATE, -1, 0);
assert(x != MAP_FAILED);
fd = open("/dev/zero", O_RDONLY);
assert(fd >= 0);
printf("%zd\n", read(fd, x, 4));
printf("%zd\n", read(fd, x + 4095, 4));
close(fd);
This brings that same standard behavior to the various RNG reader
interfaces.
While we're at it, we can streamline the loop logic a little bit.
Suggested-by: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Jann Horn <jannh@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-07 21:23:08 +02:00
|
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|
random: check for signals every PAGE_SIZE chunk of /dev/[u]random
In 1448769c9cdb ("random: check for signal_pending() outside of
need_resched() check"), Jann pointed out that we previously were only
checking the TIF_NOTIFY_SIGNAL and TIF_SIGPENDING flags if the process
had TIF_NEED_RESCHED set, which meant in practice, super long reads to
/dev/[u]random would delay signal handling by a long time. I tried this
using the below program, and indeed I wasn't able to interrupt a
/dev/urandom read until after several megabytes had been read. The bug
he fixed has always been there, and so code that reads from /dev/urandom
without checking the return value of read() has mostly worked for a long
time, for most sizes, not just for <= 256.
Maybe it makes sense to keep that code working. The reason it was so
small prior, ignoring the fact that it didn't work anyway, was likely
because /dev/random used to block, and that could happen for pretty
large lengths of time while entropy was gathered. But now, it's just a
chacha20 call, which is extremely fast and is just operating on pure
data, without having to wait for some external event. In that sense,
/dev/[u]random is a lot more like /dev/zero.
Taking a page out of /dev/zero's read_zero() function, it always returns
at least one chunk, and then checks for signals after each chunk. Chunk
sizes there are of length PAGE_SIZE. Let's just copy the same thing for
/dev/[u]random, and check for signals and cond_resched() for every
PAGE_SIZE amount of data. This makes the behavior more consistent with
expectations, and should mitigate the impact of Jann's fix for the
age-old signal check bug.
---- test program ----
#include <unistd.h>
#include <signal.h>
#include <stdio.h>
#include <sys/random.h>
static unsigned char x[~0U];
static void handle(int) { }
int main(int argc, char *argv[])
{
pid_t pid = getpid(), child;
signal(SIGUSR1, handle);
if (!(child = fork())) {
for (;;)
kill(pid, SIGUSR1);
}
pause();
printf("interrupted after reading %zd bytes\n", getrandom(x, sizeof(x), 0));
kill(child, SIGTERM);
return 0;
}
Cc: Jann Horn <jannh@google.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-06 02:36:16 +02:00
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random: allow partial reads if later user copies fail
Rather than failing entirely if a copy_to_user() fails at some point,
instead we should return a partial read for the amount that succeeded
prior, unless none succeeded at all, in which case we return -EFAULT as
before.
This makes it consistent with other reader interfaces. For example, the
following snippet for /dev/zero outputs "4" followed by "1":
int fd;
void *x = mmap(NULL, 4096, PROT_WRITE, MAP_ANONYMOUS | MAP_PRIVATE, -1, 0);
assert(x != MAP_FAILED);
fd = open("/dev/zero", O_RDONLY);
assert(fd >= 0);
printf("%zd\n", read(fd, x, 4));
printf("%zd\n", read(fd, x + 4095, 4));
close(fd);
This brings that same standard behavior to the various RNG reader
interfaces.
While we're at it, we can streamline the loop logic a little bit.
Suggested-by: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Jann Horn <jannh@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-07 21:23:08 +02:00
|
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2022-02-11 12:53:34 +01:00
|
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2022-05-19 17:31:36 -06:00
|
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|
random: do not allow user to keep crng key around on stack
The fast key erasure RNG design relies on the key that's used to be used
and then discarded. We do this, making judicious use of
memzero_explicit(). However, reads to /dev/urandom and calls to
getrandom() involve a copy_to_user(), and userspace can use FUSE or
userfaultfd, or make a massive call, dynamically remap memory addresses
as it goes, and set the process priority to idle, in order to keep a
kernel stack alive indefinitely. By probing
/proc/sys/kernel/random/entropy_avail to learn when the crng key is
refreshed, a malicious userspace could mount this attack every 5 minutes
thereafter, breaking the crng's forward secrecy.
In order to fix this, we just overwrite the stack's key with the first
32 bytes of the "free" fast key erasure output. If we're returning <= 32
bytes to the user, then we can still return those bytes directly, so
that short reads don't become slower. And for long reads, the difference
is hopefully lost in the amortization, so it doesn't change much, with
that amortization helping variously for medium reads.
We don't need to do this for get_random_bytes() and the various
kernel-space callers, and later, if we ever switch to always batching,
this won't be necessary either, so there's no need to change the API of
these functions.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Jann Horn <jannh@google.com>
Fixes: c92e040d575a ("random: add backtracking protection to the CRNG")
Fixes: 186873c549df ("random: use simpler fast key erasure flow on per-cpu keys")
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-05 16:40:51 +02:00
|
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|
random: allow partial reads if later user copies fail
Rather than failing entirely if a copy_to_user() fails at some point,
instead we should return a partial read for the amount that succeeded
prior, unless none succeeded at all, in which case we return -EFAULT as
before.
This makes it consistent with other reader interfaces. For example, the
following snippet for /dev/zero outputs "4" followed by "1":
int fd;
void *x = mmap(NULL, 4096, PROT_WRITE, MAP_ANONYMOUS | MAP_PRIVATE, -1, 0);
assert(x != MAP_FAILED);
fd = open("/dev/zero", O_RDONLY);
assert(fd >= 0);
printf("%zd\n", read(fd, x, 4));
printf("%zd\n", read(fd, x + 4095, 4));
close(fd);
This brings that same standard behavior to the various RNG reader
interfaces.
While we're at it, we can streamline the loop logic a little bit.
Suggested-by: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Jann Horn <jannh@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-07 21:23:08 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-15 00:22:05 +02:00
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2022-09-28 18:47:30 +02:00
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2022-10-05 12:54:38 +02:00
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2022-02-11 12:53:34 +01:00
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random: use rejection sampling for uniform bounded random integers
Until the very recent commits, many bounded random integers were
calculated using `get_random_u32() % max_plus_one`, which not only
incurs the price of a division -- indicating performance mostly was not
a real issue -- but also does not result in a uniformly distributed
output if max_plus_one is not a power of two. Recent commits moved to
using `prandom_u32_max(max_plus_one)`, which replaces the division with
a faster multiplication, but still does not solve the issue with
non-uniform output.
For some users, maybe this isn't a problem, and for others, maybe it is,
but for the majority of users, probably the question has never been
posed and analyzed, and nobody thought much about it, probably assuming
random is random is random. In other words, the unthinking expectation
of most users is likely that the resultant numbers are uniform.
So we implement here an efficient way of generating uniform bounded
random integers. Through use of compile-time evaluation, and avoiding
divisions as much as possible, this commit introduces no measurable
overhead. At least for hot-path uses tested, any potential difference
was lost in the noise. On both clang and gcc, code generation is pretty
small.
The new function, get_random_u32_below(), lives in random.h, rather than
prandom.h, and has a "get_random_xxx" function name, because it is
suitable for all uses, including cryptography.
In order to be efficient, we implement a kernel-specific variant of
Daniel Lemire's algorithm from "Fast Random Integer Generation in an
Interval", linked below. The kernel's variant takes advantage of
constant folding to avoid divisions entirely in the vast majority of
cases, works on both 32-bit and 64-bit architectures, and requests a
minimal amount of bytes from the RNG.
Link: https://arxiv.org/pdf/1805.10941.pdf
Cc: stable@vger.kernel.org # to ease future backports that use this api
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-10-08 20:42:54 -06:00
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2022-10-19 23:19:35 -06:00
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random: use rejection sampling for uniform bounded random integers
Until the very recent commits, many bounded random integers were
calculated using `get_random_u32() % max_plus_one`, which not only
incurs the price of a division -- indicating performance mostly was not
a real issue -- but also does not result in a uniformly distributed
output if max_plus_one is not a power of two. Recent commits moved to
using `prandom_u32_max(max_plus_one)`, which replaces the division with
a faster multiplication, but still does not solve the issue with
non-uniform output.
For some users, maybe this isn't a problem, and for others, maybe it is,
but for the majority of users, probably the question has never been
posed and analyzed, and nobody thought much about it, probably assuming
random is random is random. In other words, the unthinking expectation
of most users is likely that the resultant numbers are uniform.
So we implement here an efficient way of generating uniform bounded
random integers. Through use of compile-time evaluation, and avoiding
divisions as much as possible, this commit introduces no measurable
overhead. At least for hot-path uses tested, any potential difference
was lost in the noise. On both clang and gcc, code generation is pretty
small.
The new function, get_random_u32_below(), lives in random.h, rather than
prandom.h, and has a "get_random_xxx" function name, because it is
suitable for all uses, including cryptography.
In order to be efficient, we implement a kernel-specific variant of
Daniel Lemire's algorithm from "Fast Random Integer Generation in an
Interval", linked below. The kernel's variant takes advantage of
constant folding to avoid divisions entirely in the vast majority of
cases, works on both 32-bit and 64-bit architectures, and requests a
minimal amount of bytes from the RNG.
Link: https://arxiv.org/pdf/1805.10941.pdf
Cc: stable@vger.kernel.org # to ease future backports that use this api
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-10-08 20:42:54 -06:00
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random: clear fast pool, crng, and batches in cpuhp bring up
For the irq randomness fast pool, rather than having to use expensive
atomics, which were visibly the most expensive thing in the entire irq
handler, simply take care of the extreme edge case of resetting count to
zero in the cpuhp online handler, just after workqueues have been
reenabled. This simplifies the code a bit and lets us use vanilla
variables rather than atomics, and performance should be improved.
As well, very early on when the CPU comes up, while interrupts are still
disabled, we clear out the per-cpu crng and its batches, so that it
always starts with fresh randomness.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-13 22:48:04 +01:00
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2022-05-13 16:17:12 +02:00
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random: clear fast pool, crng, and batches in cpuhp bring up
For the irq randomness fast pool, rather than having to use expensive
atomics, which were visibly the most expensive thing in the entire irq
handler, simply take care of the extreme edge case of resetting count to
zero in the cpuhp online handler, just after workqueues have been
reenabled. This simplifies the code a bit and lets us use vanilla
variables rather than atomics, and performance should be improved.
As well, very early on when the CPU comes up, while interrupts are still
disabled, we clear out the per-cpu crng and its batches, so that it
always starts with fresh randomness.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-13 22:48:04 +01:00
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2022-10-05 12:54:38 +02:00
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random: clear fast pool, crng, and batches in cpuhp bring up
For the irq randomness fast pool, rather than having to use expensive
atomics, which were visibly the most expensive thing in the entire irq
handler, simply take care of the extreme edge case of resetting count to
zero in the cpuhp online handler, just after workqueues have been
reenabled. This simplifies the code a bit and lets us use vanilla
variables rather than atomics, and performance should be improved.
As well, very early on when the CPU comes up, while interrupts are still
disabled, we clear out the per-cpu crng and its batches, so that it
always starts with fresh randomness.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-13 22:48:04 +01:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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2022-05-08 13:20:30 +02:00
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2022-02-11 12:53:34 +01:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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random: handle archrandom with multiple longs
The archrandom interface was originally designed for x86, which supplies
RDRAND/RDSEED for receiving random words into registers, resulting in
one function to generate an int and another to generate a long. However,
other architectures don't follow this.
On arm64, the SMCCC TRNG interface can return between one and three
longs. On s390, the CPACF TRNG interface can return arbitrary amounts,
with four longs having the same cost as one. On UML, the os_getrandom()
interface can return arbitrary amounts.
So change the api signature to take a "max_longs" parameter designating
the maximum number of longs requested, and then return the number of
longs generated.
Since callers need to check this return value and loop anyway, each arch
implementation does not bother implementing its own loop to try again to
fill the maximum number of longs. Additionally, all existing callers
pass in a constant max_longs parameter. Taken together, these two things
mean that the codegen doesn't really change much for one-word-at-a-time
platforms, while performance is greatly improved on platforms such as
s390.
Acked-by: Heiko Carstens <hca@linux.ibm.com>
Acked-by: Catalin Marinas <catalin.marinas@arm.com>
Acked-by: Mark Rutland <mark.rutland@arm.com>
Acked-by: Michael Ellerman <mpe@ellerman.id.au>
Acked-by: Borislav Petkov <bp@suse.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-07-17 12:35:24 +02:00
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2022-02-11 12:53:34 +01:00
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random: handle archrandom with multiple longs
The archrandom interface was originally designed for x86, which supplies
RDRAND/RDSEED for receiving random words into registers, resulting in
one function to generate an int and another to generate a long. However,
other architectures don't follow this.
On arm64, the SMCCC TRNG interface can return between one and three
longs. On s390, the CPACF TRNG interface can return arbitrary amounts,
with four longs having the same cost as one. On UML, the os_getrandom()
interface can return arbitrary amounts.
So change the api signature to take a "max_longs" parameter designating
the maximum number of longs requested, and then return the number of
longs generated.
Since callers need to check this return value and loop anyway, each arch
implementation does not bother implementing its own loop to try again to
fill the maximum number of longs. Additionally, all existing callers
pass in a constant max_longs parameter. Taken together, these two things
mean that the codegen doesn't really change much for one-word-at-a-time
platforms, while performance is greatly improved on platforms such as
s390.
Acked-by: Heiko Carstens <hca@linux.ibm.com>
Acked-by: Catalin Marinas <catalin.marinas@arm.com>
Acked-by: Mark Rutland <mark.rutland@arm.com>
Acked-by: Michael Ellerman <mpe@ellerman.id.au>
Acked-by: Borislav Petkov <bp@suse.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-07-17 12:35:24 +02:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 16:17:12 +02:00
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random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
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|
random: use static branch for crng_ready()
Since crng_ready() is only false briefly during initialization and then
forever after becomes true, we don't need to evaluate it after, making
it a prime candidate for a static branch.
One complication, however, is that it changes state in a particular call
to credit_init_bits(), which might be made from atomic context, which
means we must kick off a workqueue to change the static key. Further
complicating things, credit_init_bits() may be called sufficiently early
on in system initialization such that system_wq is NULL.
Fortunately, there exists the nice function execute_in_process_context(),
which will immediately execute the function if !in_interrupt(), and
otherwise defer it to a workqueue. During early init, before workqueues
are available, in_interrupt() is always false, because interrupts
haven't even been enabled yet, which means the function in that case
executes immediately. Later on, after workqueues are available,
in_interrupt() might be true, but in that case, the work is queued in
system_wq and all goes well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-03 15:30:45 +02:00
|
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2022-05-09 13:40:55 +02:00
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random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
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2022-05-13 16:17:12 +02:00
|
|
|
|
random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
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|
2022-05-13 13:18:46 +02:00
|
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|
|
random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
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2022-07-14 20:28:22 +02:00
|
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|
random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
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2022-05-09 13:40:55 +02:00
|
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|
2022-07-14 20:28:22 +02:00
|
|
|
|
random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
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2022-05-09 13:53:24 +02:00
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2022-11-17 17:47:12 +01:00
|
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2022-06-07 17:28:06 +02:00
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2022-11-16 17:16:37 +01:00
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2022-05-09 13:53:24 +02:00
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random: remove ratelimiting for in-kernel unseeded randomness
The CONFIG_WARN_ALL_UNSEEDED_RANDOM debug option controls whether the
kernel warns about all unseeded randomness or just the first instance.
There's some complicated rate limiting and comparison to the previous
caller, such that even with CONFIG_WARN_ALL_UNSEEDED_RANDOM enabled,
developers still don't see all the messages or even an accurate count of
how many were missed. This is the result of basically parallel
mechanisms aimed at accomplishing more or less the same thing, added at
different points in random.c history, which sort of compete with the
first-instance-only limiting we have now.
It turns out, however, that nobody cares about the first unseeded
randomness instance of in-kernel users. The same first user has been
there for ages now, and nobody is doing anything about it. It isn't even
clear that anybody _can_ do anything about it. Most places that can do
something about it have switched over to using get_random_bytes_wait()
or wait_for_random_bytes(), which is the right thing to do, but there is
still much code that needs randomness sometimes during init, and as a
geeneral rule, if you're not using one of the _wait functions or the
readiness notifier callback, you're bound to be doing it wrong just
based on that fact alone.
So warning about this same first user that can't easily change is simply
not an effective mechanism for anything at all. Users can't do anything
about it, as the Kconfig text points out -- the problem isn't in
userspace code -- and kernel developers don't or more often can't react
to it.
Instead, show the warning for all instances when CONFIG_WARN_ALL_UNSEEDED_RANDOM
is set, so that developers can debug things need be, or if it isn't set,
don't show a warning at all.
At the same time, CONFIG_WARN_ALL_UNSEEDED_RANDOM now implies setting
random.ratelimit_disable=1 on by default, since if you care about one
you probably care about the other too. And we can clean up usage around
the related urandom_warning ratelimiter as well (whose behavior isn't
changing), so that it properly counts missed messages after the 10
message threshold is reached.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-09 16:13:18 +02:00
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2022-05-09 13:53:24 +02:00
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random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
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2022-05-09 13:53:24 +02:00
|
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|
2022-05-08 13:20:30 +02:00
|
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|
random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
|
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|
2022-05-08 13:20:30 +02:00
|
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|
random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-11-06 16:02:43 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2022-05-06 18:27:38 +02:00
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2022-02-11 12:53:34 +01:00
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random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
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2022-11-01 13:03:55 +01:00
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2022-02-11 12:53:34 +01:00
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2022-02-23 13:43:44 +01:00
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2022-02-11 12:53:34 +01:00
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2022-05-06 18:27:38 +02:00
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2022-02-11 12:53:34 +01:00
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2022-11-01 13:03:55 +01:00
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2022-02-11 12:53:34 +01:00
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2022-03-22 21:43:12 -06:00
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2022-02-11 12:53:34 +01:00
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2022-03-22 21:43:12 -06:00
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2022-02-11 12:53:34 +01:00
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2022-05-01 13:51:34 +02:00
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2022-06-30 19:12:29 +00:00
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2022-11-17 17:47:12 +01:00
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2022-05-01 13:51:34 +02:00
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2022-02-11 12:53:34 +01:00
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random: split initialization into early step and later step
The full RNG initialization relies on some timestamps, made possible
with initialization functions like time_init() and timekeeping_init().
However, these are only available rather late in initialization.
Meanwhile, other things, such as memory allocator functions, make use of
the RNG much earlier.
So split RNG initialization into two phases. We can provide arch
randomness very early on, and then later, after timekeeping and such are
available, initialize the rest.
This ensures that, for example, slabs are properly randomized if RDRAND
is available. Without this, CONFIG_SLAB_FREELIST_RANDOM=y loses a degree
of its security, because its random seed is potentially deterministic,
since it hasn't yet incorporated RDRAND. It also makes it possible to
use a better seed in kfence, which currently relies on only the cycle
counter.
Another positive consequence is that on systems with RDRAND, running
with CONFIG_WARN_ALL_UNSEEDED_RANDOM=y results in no warnings at all.
One subtle side effect of this change is that on systems with no RDRAND,
RDTSC is now only queried by random_init() once, committing the moment
of the function call, instead of multiple times as before. This is
intentional, as the multiple RDTSCs in a loop before weren't
accomplishing very much, with jitter being better provided by
try_to_generate_entropy(). Plus, filling blocks with RDTSC is still
being done in extract_entropy(), which is necessarily called before
random bytes are served anyway.
Cc: Andrew Morton <akpm@linux-foundation.org>
Reviewed-by: Kees Cook <keescook@chromium.org>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-09-26 17:43:14 +02:00
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2022-02-11 12:53:34 +01:00
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random: split initialization into early step and later step
The full RNG initialization relies on some timestamps, made possible
with initialization functions like time_init() and timekeeping_init().
However, these are only available rather late in initialization.
Meanwhile, other things, such as memory allocator functions, make use of
the RNG much earlier.
So split RNG initialization into two phases. We can provide arch
randomness very early on, and then later, after timekeeping and such are
available, initialize the rest.
This ensures that, for example, slabs are properly randomized if RDRAND
is available. Without this, CONFIG_SLAB_FREELIST_RANDOM=y loses a degree
of its security, because its random seed is potentially deterministic,
since it hasn't yet incorporated RDRAND. It also makes it possible to
use a better seed in kfence, which currently relies on only the cycle
counter.
Another positive consequence is that on systems with RDRAND, running
with CONFIG_WARN_ALL_UNSEEDED_RANDOM=y results in no warnings at all.
One subtle side effect of this change is that on systems with no RDRAND,
RDTSC is now only queried by random_init() once, committing the moment
of the function call, instead of multiple times as before. This is
intentional, as the multiple RDTSCs in a loop before weren't
accomplishing very much, with jitter being better provided by
try_to_generate_entropy(). Plus, filling blocks with RDTSC is still
being done in extract_entropy(), which is necessarily called before
random bytes are served anyway.
Cc: Andrew Morton <akpm@linux-foundation.org>
Reviewed-by: Kees Cook <keescook@chromium.org>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-09-26 17:43:14 +02:00
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2022-02-11 12:53:34 +01:00
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random: handle archrandom with multiple longs
The archrandom interface was originally designed for x86, which supplies
RDRAND/RDSEED for receiving random words into registers, resulting in
one function to generate an int and another to generate a long. However,
other architectures don't follow this.
On arm64, the SMCCC TRNG interface can return between one and three
longs. On s390, the CPACF TRNG interface can return arbitrary amounts,
with four longs having the same cost as one. On UML, the os_getrandom()
interface can return arbitrary amounts.
So change the api signature to take a "max_longs" parameter designating
the maximum number of longs requested, and then return the number of
longs generated.
Since callers need to check this return value and loop anyway, each arch
implementation does not bother implementing its own loop to try again to
fill the maximum number of longs. Additionally, all existing callers
pass in a constant max_longs parameter. Taken together, these two things
mean that the codegen doesn't really change much for one-word-at-a-time
platforms, while performance is greatly improved on platforms such as
s390.
Acked-by: Heiko Carstens <hca@linux.ibm.com>
Acked-by: Catalin Marinas <catalin.marinas@arm.com>
Acked-by: Mark Rutland <mark.rutland@arm.com>
Acked-by: Michael Ellerman <mpe@ellerman.id.au>
Acked-by: Borislav Petkov <bp@suse.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-07-17 12:35:24 +02:00
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random: split initialization into early step and later step
The full RNG initialization relies on some timestamps, made possible
with initialization functions like time_init() and timekeeping_init().
However, these are only available rather late in initialization.
Meanwhile, other things, such as memory allocator functions, make use of
the RNG much earlier.
So split RNG initialization into two phases. We can provide arch
randomness very early on, and then later, after timekeeping and such are
available, initialize the rest.
This ensures that, for example, slabs are properly randomized if RDRAND
is available. Without this, CONFIG_SLAB_FREELIST_RANDOM=y loses a degree
of its security, because its random seed is potentially deterministic,
since it hasn't yet incorporated RDRAND. It also makes it possible to
use a better seed in kfence, which currently relies on only the cycle
counter.
Another positive consequence is that on systems with RDRAND, running
with CONFIG_WARN_ALL_UNSEEDED_RANDOM=y results in no warnings at all.
One subtle side effect of this change is that on systems with no RDRAND,
RDTSC is now only queried by random_init() once, committing the moment
of the function call, instead of multiple times as before. This is
intentional, as the multiple RDTSCs in a loop before weren't
accomplishing very much, with jitter being better provided by
try_to_generate_entropy(). Plus, filling blocks with RDTSC is still
being done in extract_entropy(), which is necessarily called before
random bytes are served anyway.
Cc: Andrew Morton <akpm@linux-foundation.org>
Reviewed-by: Kees Cook <keescook@chromium.org>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-09-26 17:43:14 +02:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
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2022-03-31 11:01:01 -04:00
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random: handle archrandom with multiple longs
The archrandom interface was originally designed for x86, which supplies
RDRAND/RDSEED for receiving random words into registers, resulting in
one function to generate an int and another to generate a long. However,
other architectures don't follow this.
On arm64, the SMCCC TRNG interface can return between one and three
longs. On s390, the CPACF TRNG interface can return arbitrary amounts,
with four longs having the same cost as one. On UML, the os_getrandom()
interface can return arbitrary amounts.
So change the api signature to take a "max_longs" parameter designating
the maximum number of longs requested, and then return the number of
longs generated.
Since callers need to check this return value and loop anyway, each arch
implementation does not bother implementing its own loop to try again to
fill the maximum number of longs. Additionally, all existing callers
pass in a constant max_longs parameter. Taken together, these two things
mean that the codegen doesn't really change much for one-word-at-a-time
platforms, while performance is greatly improved on platforms such as
s390.
Acked-by: Heiko Carstens <hca@linux.ibm.com>
Acked-by: Catalin Marinas <catalin.marinas@arm.com>
Acked-by: Mark Rutland <mark.rutland@arm.com>
Acked-by: Michael Ellerman <mpe@ellerman.id.au>
Acked-by: Borislav Petkov <bp@suse.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-07-17 12:35:24 +02:00
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2022-10-29 01:18:04 +02:00
|
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|
random: handle archrandom with multiple longs
The archrandom interface was originally designed for x86, which supplies
RDRAND/RDSEED for receiving random words into registers, resulting in
one function to generate an int and another to generate a long. However,
other architectures don't follow this.
On arm64, the SMCCC TRNG interface can return between one and three
longs. On s390, the CPACF TRNG interface can return arbitrary amounts,
with four longs having the same cost as one. On UML, the os_getrandom()
interface can return arbitrary amounts.
So change the api signature to take a "max_longs" parameter designating
the maximum number of longs requested, and then return the number of
longs generated.
Since callers need to check this return value and loop anyway, each arch
implementation does not bother implementing its own loop to try again to
fill the maximum number of longs. Additionally, all existing callers
pass in a constant max_longs parameter. Taken together, these two things
mean that the codegen doesn't really change much for one-word-at-a-time
platforms, while performance is greatly improved on platforms such as
s390.
Acked-by: Heiko Carstens <hca@linux.ibm.com>
Acked-by: Catalin Marinas <catalin.marinas@arm.com>
Acked-by: Mark Rutland <mark.rutland@arm.com>
Acked-by: Michael Ellerman <mpe@ellerman.id.au>
Acked-by: Borislav Petkov <bp@suse.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-07-17 12:35:24 +02:00
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2022-10-29 01:18:04 +02:00
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|
random: handle archrandom with multiple longs
The archrandom interface was originally designed for x86, which supplies
RDRAND/RDSEED for receiving random words into registers, resulting in
one function to generate an int and another to generate a long. However,
other architectures don't follow this.
On arm64, the SMCCC TRNG interface can return between one and three
longs. On s390, the CPACF TRNG interface can return arbitrary amounts,
with four longs having the same cost as one. On UML, the os_getrandom()
interface can return arbitrary amounts.
So change the api signature to take a "max_longs" parameter designating
the maximum number of longs requested, and then return the number of
longs generated.
Since callers need to check this return value and loop anyway, each arch
implementation does not bother implementing its own loop to try again to
fill the maximum number of longs. Additionally, all existing callers
pass in a constant max_longs parameter. Taken together, these two things
mean that the codegen doesn't really change much for one-word-at-a-time
platforms, while performance is greatly improved on platforms such as
s390.
Acked-by: Heiko Carstens <hca@linux.ibm.com>
Acked-by: Catalin Marinas <catalin.marinas@arm.com>
Acked-by: Mark Rutland <mark.rutland@arm.com>
Acked-by: Michael Ellerman <mpe@ellerman.id.au>
Acked-by: Borislav Petkov <bp@suse.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-07-17 12:35:24 +02:00
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2022-02-11 12:53:34 +01:00
|
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|
random: handle archrandom with multiple longs
The archrandom interface was originally designed for x86, which supplies
RDRAND/RDSEED for receiving random words into registers, resulting in
one function to generate an int and another to generate a long. However,
other architectures don't follow this.
On arm64, the SMCCC TRNG interface can return between one and three
longs. On s390, the CPACF TRNG interface can return arbitrary amounts,
with four longs having the same cost as one. On UML, the os_getrandom()
interface can return arbitrary amounts.
So change the api signature to take a "max_longs" parameter designating
the maximum number of longs requested, and then return the number of
longs generated.
Since callers need to check this return value and loop anyway, each arch
implementation does not bother implementing its own loop to try again to
fill the maximum number of longs. Additionally, all existing callers
pass in a constant max_longs parameter. Taken together, these two things
mean that the codegen doesn't really change much for one-word-at-a-time
platforms, while performance is greatly improved on platforms such as
s390.
Acked-by: Heiko Carstens <hca@linux.ibm.com>
Acked-by: Catalin Marinas <catalin.marinas@arm.com>
Acked-by: Mark Rutland <mark.rutland@arm.com>
Acked-by: Michael Ellerman <mpe@ellerman.id.au>
Acked-by: Borislav Petkov <bp@suse.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-07-17 12:35:24 +02:00
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2022-02-11 12:53:34 +01:00
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|
random: split initialization into early step and later step
The full RNG initialization relies on some timestamps, made possible
with initialization functions like time_init() and timekeeping_init().
However, these are only available rather late in initialization.
Meanwhile, other things, such as memory allocator functions, make use of
the RNG much earlier.
So split RNG initialization into two phases. We can provide arch
randomness very early on, and then later, after timekeeping and such are
available, initialize the rest.
This ensures that, for example, slabs are properly randomized if RDRAND
is available. Without this, CONFIG_SLAB_FREELIST_RANDOM=y loses a degree
of its security, because its random seed is potentially deterministic,
since it hasn't yet incorporated RDRAND. It also makes it possible to
use a better seed in kfence, which currently relies on only the cycle
counter.
Another positive consequence is that on systems with RDRAND, running
with CONFIG_WARN_ALL_UNSEEDED_RANDOM=y results in no warnings at all.
One subtle side effect of this change is that on systems with no RDRAND,
RDTSC is now only queried by random_init() once, committing the moment
of the function call, instead of multiple times as before. This is
intentional, as the multiple RDTSCs in a loop before weren't
accomplishing very much, with jitter being better provided by
try_to_generate_entropy(). Plus, filling blocks with RDTSC is still
being done in extract_entropy(), which is necessarily called before
random bytes are served anyway.
Cc: Andrew Morton <akpm@linux-foundation.org>
Reviewed-by: Kees Cook <keescook@chromium.org>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-09-26 17:43:14 +02:00
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2022-09-27 11:26:44 +02:00
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2022-05-05 02:20:22 +02:00
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random: split initialization into early step and later step
The full RNG initialization relies on some timestamps, made possible
with initialization functions like time_init() and timekeeping_init().
However, these are only available rather late in initialization.
Meanwhile, other things, such as memory allocator functions, make use of
the RNG much earlier.
So split RNG initialization into two phases. We can provide arch
randomness very early on, and then later, after timekeeping and such are
available, initialize the rest.
This ensures that, for example, slabs are properly randomized if RDRAND
is available. Without this, CONFIG_SLAB_FREELIST_RANDOM=y loses a degree
of its security, because its random seed is potentially deterministic,
since it hasn't yet incorporated RDRAND. It also makes it possible to
use a better seed in kfence, which currently relies on only the cycle
counter.
Another positive consequence is that on systems with RDRAND, running
with CONFIG_WARN_ALL_UNSEEDED_RANDOM=y results in no warnings at all.
One subtle side effect of this change is that on systems with no RDRAND,
RDTSC is now only queried by random_init() once, committing the moment
of the function call, instead of multiple times as before. This is
intentional, as the multiple RDTSCs in a loop before weren't
accomplishing very much, with jitter being better provided by
try_to_generate_entropy(). Plus, filling blocks with RDTSC is still
being done in extract_entropy(), which is necessarily called before
random bytes are served anyway.
Cc: Andrew Morton <akpm@linux-foundation.org>
Reviewed-by: Kees Cook <keescook@chromium.org>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-09-26 17:43:14 +02:00
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2022-11-17 17:47:12 +01:00
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random: split initialization into early step and later step
The full RNG initialization relies on some timestamps, made possible
with initialization functions like time_init() and timekeeping_init().
However, these are only available rather late in initialization.
Meanwhile, other things, such as memory allocator functions, make use of
the RNG much earlier.
So split RNG initialization into two phases. We can provide arch
randomness very early on, and then later, after timekeeping and such are
available, initialize the rest.
This ensures that, for example, slabs are properly randomized if RDRAND
is available. Without this, CONFIG_SLAB_FREELIST_RANDOM=y loses a degree
of its security, because its random seed is potentially deterministic,
since it hasn't yet incorporated RDRAND. It also makes it possible to
use a better seed in kfence, which currently relies on only the cycle
counter.
Another positive consequence is that on systems with RDRAND, running
with CONFIG_WARN_ALL_UNSEEDED_RANDOM=y results in no warnings at all.
One subtle side effect of this change is that on systems with no RDRAND,
RDTSC is now only queried by random_init() once, committing the moment
of the function call, instead of multiple times as before. This is
intentional, as the multiple RDTSCs in a loop before weren't
accomplishing very much, with jitter being better provided by
try_to_generate_entropy(). Plus, filling blocks with RDTSC is still
being done in extract_entropy(), which is necessarily called before
random bytes are served anyway.
Cc: Andrew Morton <akpm@linux-foundation.org>
Reviewed-by: Kees Cook <keescook@chromium.org>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-09-26 17:43:14 +02:00
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2022-05-05 02:20:22 +02:00
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random: use simpler fast key erasure flow on per-cpu keys
Rather than the clunky NUMA full ChaCha state system we had prior, this
commit is closer to the original "fast key erasure RNG" proposal from
<https://blog.cr.yp.to/20170723-random.html>, by simply treating ChaCha
keys on a per-cpu basis.
All entropy is extracted to a base crng key of 32 bytes. This base crng
has a birthdate and a generation counter. When we go to take bytes from
the crng, we first check if the birthdate is too old; if it is, we
reseed per usual. Then we start working on a per-cpu crng.
This per-cpu crng makes sure that it has the same generation counter as
the base crng. If it doesn't, it does fast key erasure with the base
crng key and uses the output as its new per-cpu key, and then updates
its local generation counter. Then, using this per-cpu state, we do
ordinary fast key erasure. Half of this first block is used to overwrite
the per-cpu crng key for the next call -- this is the fast key erasure
RNG idea -- and the other half, along with the ChaCha state, is returned
to the caller. If the caller desires more than this remaining half, it
can generate more ChaCha blocks, unlocked, using the now detached ChaCha
state that was just returned. Crypto-wise, this is more or less what we
were doing before, but this simply makes it more explicit and ensures
that we always have backtrack protection by not playing games with a
shared block counter.
The flow looks like this:
──extract()──► base_crng.key ◄──memcpy()───┐
│ │
└──chacha()──────┬─► new_base_key
└─► crngs[n].key ◄──memcpy()───┐
│ │
└──chacha()───┬─► new_key
└─► random_bytes
│
└────►
There are a few hairy details around early init. Just as was done
before, prior to having gathered enough entropy, crng_fast_load() and
crng_slow_load() dump bytes directly into the base crng, and when we go
to take bytes from the crng, in that case, we're doing fast key erasure
with the base crng rather than the fast unlocked per-cpu crngs. This is
fine as that's only the state of affairs during very early boot; once
the crng initializes we never use these paths again.
In the process of all this, the APIs into the crng become a bit simpler:
we have get_random_bytes(buf, len) and get_random_bytes_user(buf, len),
which both do what you'd expect. All of the details of fast key erasure
and per-cpu selection happen only in a very short critical section of
crng_make_state(), which selects the right per-cpu key, does the fast
key erasure, and returns a local state to the caller's stack. So, we no
longer have a need for a separate backtrack function, as this happens
all at once here. The API then allows us to extend backtrack protection
to batched entropy without really having to do much at all.
The result is a bit simpler than before and has fewer foot guns. The
init time state machine also gets a lot simpler as we don't need to wait
for workqueues to come online and do deferred work. And the multi-core
performance should be increased significantly, by virtue of having hardly
any locking on the fast path.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Jann Horn <jannh@google.com>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-07 15:08:49 +01:00
|
|
|
|
2022-06-07 17:28:06 +02:00
|
|
|
|
random: split initialization into early step and later step
The full RNG initialization relies on some timestamps, made possible
with initialization functions like time_init() and timekeeping_init().
However, these are only available rather late in initialization.
Meanwhile, other things, such as memory allocator functions, make use of
the RNG much earlier.
So split RNG initialization into two phases. We can provide arch
randomness very early on, and then later, after timekeeping and such are
available, initialize the rest.
This ensures that, for example, slabs are properly randomized if RDRAND
is available. Without this, CONFIG_SLAB_FREELIST_RANDOM=y loses a degree
of its security, because its random seed is potentially deterministic,
since it hasn't yet incorporated RDRAND. It also makes it possible to
use a better seed in kfence, which currently relies on only the cycle
counter.
Another positive consequence is that on systems with RDRAND, running
with CONFIG_WARN_ALL_UNSEEDED_RANDOM=y results in no warnings at all.
One subtle side effect of this change is that on systems with no RDRAND,
RDTSC is now only queried by random_init() once, committing the moment
of the function call, instead of multiple times as before. This is
intentional, as the multiple RDTSCs in a loop before weren't
accomplishing very much, with jitter being better provided by
try_to_generate_entropy(). Plus, filling blocks with RDTSC is still
being done in extract_entropy(), which is necessarily called before
random bytes are served anyway.
Cc: Andrew Morton <akpm@linux-foundation.org>
Reviewed-by: Kees Cook <keescook@chromium.org>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-09-26 17:43:14 +02:00
|
|
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|
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|
|
|
|
2022-06-07 17:28:06 +02:00
|
|
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random: split initialization into early step and later step
The full RNG initialization relies on some timestamps, made possible
with initialization functions like time_init() and timekeeping_init().
However, these are only available rather late in initialization.
Meanwhile, other things, such as memory allocator functions, make use of
the RNG much earlier.
So split RNG initialization into two phases. We can provide arch
randomness very early on, and then later, after timekeeping and such are
available, initialize the rest.
This ensures that, for example, slabs are properly randomized if RDRAND
is available. Without this, CONFIG_SLAB_FREELIST_RANDOM=y loses a degree
of its security, because its random seed is potentially deterministic,
since it hasn't yet incorporated RDRAND. It also makes it possible to
use a better seed in kfence, which currently relies on only the cycle
counter.
Another positive consequence is that on systems with RDRAND, running
with CONFIG_WARN_ALL_UNSEEDED_RANDOM=y results in no warnings at all.
One subtle side effect of this change is that on systems with no RDRAND,
RDTSC is now only queried by random_init() once, committing the moment
of the function call, instead of multiple times as before. This is
intentional, as the multiple RDTSCs in a loop before weren't
accomplishing very much, with jitter being better provided by
try_to_generate_entropy(). Plus, filling blocks with RDTSC is still
being done in extract_entropy(), which is necessarily called before
random bytes are served anyway.
Cc: Andrew Morton <akpm@linux-foundation.org>
Reviewed-by: Kees Cook <keescook@chromium.org>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-09-26 17:43:14 +02:00
|
|
|
|
random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
|
|
|
|
2022-11-17 17:47:12 +01:00
|
|
|
|
2016-06-12 18:13:36 -04:00
|
|
|
|
2022-05-01 13:51:34 +02:00
|
|
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|
|
random: split initialization into early step and later step
The full RNG initialization relies on some timestamps, made possible
with initialization functions like time_init() and timekeeping_init().
However, these are only available rather late in initialization.
Meanwhile, other things, such as memory allocator functions, make use of
the RNG much earlier.
So split RNG initialization into two phases. We can provide arch
randomness very early on, and then later, after timekeeping and such are
available, initialize the rest.
This ensures that, for example, slabs are properly randomized if RDRAND
is available. Without this, CONFIG_SLAB_FREELIST_RANDOM=y loses a degree
of its security, because its random seed is potentially deterministic,
since it hasn't yet incorporated RDRAND. It also makes it possible to
use a better seed in kfence, which currently relies on only the cycle
counter.
Another positive consequence is that on systems with RDRAND, running
with CONFIG_WARN_ALL_UNSEEDED_RANDOM=y results in no warnings at all.
One subtle side effect of this change is that on systems with no RDRAND,
RDTSC is now only queried by random_init() once, committing the moment
of the function call, instead of multiple times as before. This is
intentional, as the multiple RDTSCs in a loop before weren't
accomplishing very much, with jitter being better provided by
try_to_generate_entropy(). Plus, filling blocks with RDTSC is still
being done in extract_entropy(), which is necessarily called before
random bytes are served anyway.
Cc: Andrew Morton <akpm@linux-foundation.org>
Reviewed-by: Kees Cook <keescook@chromium.org>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-09-26 17:43:14 +02:00
|
|
|
|
|
|
|
|
|
2022-02-11 12:53:34 +01:00
|
|
|
|
2016-06-12 18:13:36 -04:00
|
|
|
|
2012-07-04 11:16:01 -04:00
|
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|
|
2016-06-12 18:13:36 -04:00
|
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|
2012-07-04 11:16:01 -04:00
|
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|
2016-06-12 18:13:36 -04:00
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2012-07-04 11:16:01 -04:00
|
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2022-05-13 13:18:46 +02:00
|
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2012-07-04 11:16:01 -04:00
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random: insist on random_get_entropy() existing in order to simplify
All platforms are now guaranteed to provide some value for
random_get_entropy(). In case some bug leads to this not being so, we
print a warning, because that indicates that something is really very
wrong (and likely other things are impacted too). This should never be
hit, but it's a good and cheap way of finding out if something ever is
problematic.
Since we now have viable fallback code for random_get_entropy() on all
platforms, which is, in the worst case, not worse than jiffies, we can
count on getting the best possible value out of it. That means there's
no longer a use for using jiffies as entropy input. It also means we no
longer have a reason for doing the round-robin register flow in the IRQ
handler, which was always of fairly dubious value.
Instead we can greatly simplify the IRQ handler inputs and also unify
the construction between 64-bits and 32-bits. We now collect the cycle
counter and the return address, since those are the two things that
matter. Because the return address and the irq number are likely
related, to the extent we mix in the irq number, we can just xor it into
the top unchanging bytes of the return address, rather than the bottom
changing bytes of the cycle counter as before. Then, we can do a fixed 2
rounds of SipHash/HSipHash. Finally, we use the same construction of
hashing only half of the [H]SipHash state on 32-bit and 64-bit. We're
not actually discarding any entropy, since that entropy is carried
through until the next time. And more importantly, it lets us do the
same sponge-like construction everywhere.
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-12 19:59:57 +02:00
|
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|
2012-07-04 11:16:01 -04:00
|
|
|
|
2013-09-12 14:27:22 -04:00
|
|
|
|
random: insist on random_get_entropy() existing in order to simplify
All platforms are now guaranteed to provide some value for
random_get_entropy(). In case some bug leads to this not being so, we
print a warning, because that indicates that something is really very
wrong (and likely other things are impacted too). This should never be
hit, but it's a good and cheap way of finding out if something ever is
problematic.
Since we now have viable fallback code for random_get_entropy() on all
platforms, which is, in the worst case, not worse than jiffies, we can
count on getting the best possible value out of it. That means there's
no longer a use for using jiffies as entropy input. It also means we no
longer have a reason for doing the round-robin register flow in the IRQ
handler, which was always of fairly dubious value.
Instead we can greatly simplify the IRQ handler inputs and also unify
the construction between 64-bits and 32-bits. We now collect the cycle
counter and the return address, since those are the two things that
matter. Because the return address and the irq number are likely
related, to the extent we mix in the irq number, we can just xor it into
the top unchanging bytes of the return address, rather than the bottom
changing bytes of the cycle counter as before. Then, we can do a fixed 2
rounds of SipHash/HSipHash. Finally, we use the same construction of
hashing only half of the [H]SipHash state on 32-bit and 64-bit. We're
not actually discarding any entropy, since that entropy is carried
through until the next time. And more importantly, it lets us do the
same sponge-like construction everywhere.
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-12 19:59:57 +02:00
|
|
|
|
2022-05-13 13:18:46 +02:00
|
|
|
|
2013-09-12 14:27:22 -04:00
|
|
|
|
2012-07-04 11:16:01 -04:00
|
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|
|
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|
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|
|
2022-02-11 12:53:34 +01:00
|
|
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|
2022-11-06 16:02:43 +01:00
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2022-02-11 12:53:34 +01:00
|
|
|
|
2022-11-06 16:02:43 +01:00
|
|
|
|
2022-02-11 12:53:34 +01:00
|
|
|
|
2022-05-13 13:18:46 +02:00
|
|
|
|
random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
|
|
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|
|
|
|
|
|
2022-02-11 12:53:34 +01:00
|
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|
|
2022-09-04 12:17:53 +02:00
|
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|
|
2022-09-20 16:12:00 +02:00
|
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|
2022-02-11 12:53:34 +01:00
|
|
|
|
2022-11-06 16:02:43 +01:00
|
|
|
|
2022-09-04 12:17:53 +02:00
|
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2022-02-11 12:53:34 +01:00
|
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2022-11-01 13:03:55 +01:00
|
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2022-02-11 12:53:34 +01:00
|
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|
|
2022-06-07 17:00:16 +02:00
|
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|
2022-02-11 12:53:34 +01:00
|
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|
2022-05-13 13:18:46 +02:00
|
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2022-03-22 21:43:12 -06:00
|
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|
2022-05-13 13:18:46 +02:00
|
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2022-02-11 12:53:34 +01:00
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random: do not export add_vmfork_randomness() unless needed
Since add_vmfork_randomness() is only called from vmgenid.o, we can
guard it in CONFIG_VMGENID, similarly to how we do with
add_disk_randomness() and CONFIG_BLOCK. If we ever have multiple things
calling into add_vmfork_randomness(), we can add another shared Kconfig
symbol for that, but for now, this is good enough. Even though
add_vmfork_randomess() is a pretty small function, removing it means
that there are only calls to crng_reseed(false) and none to
crng_reseed(true), which means the compiler can constant propagate the
false, removing branches from crng_reseed() and its descendants.
Additionally, we don't even need the symbol to be exported if
CONFIG_VMGENID is not a module, so conditionalize that too.
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-01 15:14:04 +01:00
|
|
|
|
2022-03-01 20:22:39 +01:00
|
|
|
|
|
|
|
|
|
2022-02-23 13:43:44 +01:00
|
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|
2022-05-13 16:17:12 +02:00
|
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|
|
2022-02-23 13:43:44 +01:00
|
|
|
|
2022-05-13 13:18:46 +02:00
|
|
|
|
2022-02-23 13:43:44 +01:00
|
|
|
|
2022-11-17 17:47:12 +01:00
|
|
|
|
2022-02-23 13:43:44 +01:00
|
|
|
|
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|
|
|
|
2022-03-01 20:22:39 +01:00
|
|
|
|
2022-02-23 13:43:44 +01:00
|
|
|
|
random: do not export add_vmfork_randomness() unless needed
Since add_vmfork_randomness() is only called from vmgenid.o, we can
guard it in CONFIG_VMGENID, similarly to how we do with
add_disk_randomness() and CONFIG_BLOCK. If we ever have multiple things
calling into add_vmfork_randomness(), we can add another shared Kconfig
symbol for that, but for now, this is good enough. Even though
add_vmfork_randomess() is a pretty small function, removing it means
that there are only calls to crng_reseed(false) and none to
crng_reseed(true), which means the compiler can constant propagate the
false, removing branches from crng_reseed() and its descendants.
Additionally, we don't even need the symbol to be exported if
CONFIG_VMGENID is not a module, so conditionalize that too.
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-01 15:14:04 +01:00
|
|
|
|
2022-02-23 13:43:44 +01:00
|
|
|
|
random: do not export add_vmfork_randomness() unless needed
Since add_vmfork_randomness() is only called from vmgenid.o, we can
guard it in CONFIG_VMGENID, similarly to how we do with
add_disk_randomness() and CONFIG_BLOCK. If we ever have multiple things
calling into add_vmfork_randomness(), we can add another shared Kconfig
symbol for that, but for now, this is good enough. Even though
add_vmfork_randomess() is a pretty small function, removing it means
that there are only calls to crng_reseed(false) and none to
crng_reseed(true), which means the compiler can constant propagate the
false, removing branches from crng_reseed() and its descendants.
Additionally, we don't even need the symbol to be exported if
CONFIG_VMGENID is not a module, so conditionalize that too.
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-01 15:14:04 +01:00
|
|
|
|
2022-03-01 20:22:39 +01:00
|
|
|
|
2022-05-13 16:17:12 +02:00
|
|
|
|
2022-03-01 20:22:39 +01:00
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2022-05-13 16:17:12 +02:00
|
|
|
|
2022-03-01 20:22:39 +01:00
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
random: do not export add_vmfork_randomness() unless needed
Since add_vmfork_randomness() is only called from vmgenid.o, we can
guard it in CONFIG_VMGENID, similarly to how we do with
add_disk_randomness() and CONFIG_BLOCK. If we ever have multiple things
calling into add_vmfork_randomness(), we can add another shared Kconfig
symbol for that, but for now, this is good enough. Even though
add_vmfork_randomess() is a pretty small function, removing it means
that there are only calls to crng_reseed(false) and none to
crng_reseed(true), which means the compiler can constant propagate the
false, removing branches from crng_reseed() and its descendants.
Additionally, we don't even need the symbol to be exported if
CONFIG_VMGENID is not a module, so conditionalize that too.
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-01 15:14:04 +01:00
|
|
|
|
2022-02-23 13:43:44 +01:00
|
|
|
|
2022-02-11 12:53:34 +01:00
|
|
|
|
random: use SipHash as interrupt entropy accumulator
The current fast_mix() function is a piece of classic mailing list
crypto, where it just sort of sprung up by an anonymous author without a
lot of real analysis of what precisely it was accomplishing. As an ARX
permutation alone, there are some easily searchable differential trails
in it, and as a means of preventing malicious interrupts, it completely
fails, since it xors new data into the entire state every time. It can't
really be analyzed as a random permutation, because it clearly isn't,
and it can't be analyzed as an interesting linear algebraic structure
either, because it's also not that. There really is very little one can
say about it in terms of entropy accumulation. It might diffuse bits,
some of the time, maybe, we hope, I guess. But for the most part, it
fails to accomplish anything concrete.
As a reminder, the simple goal of add_interrupt_randomness() is to
simply accumulate entropy until ~64 interrupts have elapsed, and then
dump it into the main input pool, which uses a cryptographic hash.
It would be nice to have something cryptographically strong in the
interrupt handler itself, in case a malicious interrupt compromises a
per-cpu fast pool within the 64 interrupts / 1 second window, and then
inside of that same window somehow can control its return address and
cycle counter, even if that's a bit far fetched. However, with a very
CPU-limited budget, actually doing that remains an active research
project (and perhaps there'll be something useful for Linux to come out
of it). And while the abundance of caution would be nice, this isn't
*currently* the security model, and we don't yet have a fast enough
solution to make it our security model. Plus there's not exactly a
pressing need to do that. (And for the avoidance of doubt, the actual
cluster of 64 accumulated interrupts still gets dumped into our
cryptographically secure input pool.)
So, for now we are going to stick with the existing interrupt security
model, which assumes that each cluster of 64 interrupt data samples is
mostly non-malicious and not colluding with an infoleaker. With this as
our goal, we have a few more choices, simply aiming to accumulate
entropy, while discarding the least amount of it.
We know from <https://eprint.iacr.org/2019/198> that random oracles,
instantiated as computational hash functions, make good entropy
accumulators and extractors, which is the justification for using
BLAKE2s in the main input pool. As mentioned, we don't have that luxury
here, but we also don't have the same security model requirements,
because we're assuming that there aren't malicious inputs. A
pseudorandom function instance can approximately behave like a random
oracle, provided that the key is uniformly random. But since we're not
concerned with malicious inputs, we can pick a fixed key, which is not
secret, knowing that "nature" won't interact with a sufficiently chosen
fixed key by accident. So we pick a PRF with a fixed initial key, and
accumulate into it continuously, dumping the result every 64 interrupts
into our cryptographically secure input pool.
For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on
32-bit, which are already in use in the kernel's hsiphash family of
functions and achieve the same performance as the function they replace.
It would be nice to do two rounds, but we don't exactly have the CPU
budget handy for that, and one round alone is already sufficient.
As mentioned, we start with a fixed initial key (zeros is fine), and
allow SipHash's symmetry breaking constants to turn that into a useful
starting point. Also, since we're dumping the result (or half of it on
64-bit so as to tax our hash function the same amount on all platforms)
into the cryptographically secure input pool, there's no point in
finalizing SipHash's output, since it'll wind up being finalized by
something much stronger. This means that all we need to do is use the
ordinary round function word-by-word, as normal SipHash does.
Simplified, the flow is as follows:
Initialize:
siphash_state_t state;
siphash_init(&state, key={0, 0, 0, 0});
Update (accumulate) on interrupt:
siphash_update(&state, interrupt_data_and_timing);
Dump into input pool after 64 interrupts:
blake2s_update(&input_pool, &state, sizeof(state) / 2);
The result of all of this is that the security model is unchanged from
before -- we assume non-malicious inputs -- yet we now implement that
model with a stronger argument. I would like to emphasize, again, that
the purpose of this commit is to improve the existing design, by making
it analyzable, without changing any fundamental assumptions. There may
well be value down the road in changing up the existing design, using
something cryptographically strong, or simply using a ring buffer of
samples rather than having a fast_mix() at all, or changing which and
how much data we collect each interrupt so that we can use something
linear, or a variety of other ideas. This commit does not invalidate the
potential for those in the future.
For example, in the future, if we're able to characterize the data we're
collecting on each interrupt, we may be able to inch toward information
theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s
= ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good
accumulators for 2-monotone distributions, which would apply to
timestamp counters, like random_get_entropy() or jiffies, but would not
apply to our current combination of the two values, or to the various
function addresses and register values we mix in. Alternatively,
<https://eprint.iacr.org/2021/1002> shows that max-period linear
functions with no non-trivial invariant subspace make good extractors,
used in the form `s = f(s) ^ x`. However, this only works if the input
data is both identical and independent, and obviously a collection of
address values and counters fails; so it goes with theoretical papers.
Future directions here may involve trying to characterize more precisely
what we actually need to collect in the interrupt handler, and building
something specific around that.
However, as mentioned, the morass of data we're gathering at the
interrupt handler presently defies characterization, and so we use
SipHash for now, which works well and performs well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 14:58:44 +01:00
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2022-02-11 12:53:34 +01:00
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random: clear fast pool, crng, and batches in cpuhp bring up
For the irq randomness fast pool, rather than having to use expensive
atomics, which were visibly the most expensive thing in the entire irq
handler, simply take care of the extreme edge case of resetting count to
zero in the cpuhp online handler, just after workqueues have been
reenabled. This simplifies the code a bit and lets us use vanilla
variables rather than atomics, and performance should be improved.
As well, very early on when the CPU comes up, while interrupts are still
disabled, we clear out the per-cpu crng and its batches, so that it
always starts with fresh randomness.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-13 22:48:04 +01:00
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2022-09-22 18:46:04 +02:00
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2022-02-11 12:53:34 +01:00
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2022-09-22 18:46:04 +02:00
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random: use SipHash as interrupt entropy accumulator
The current fast_mix() function is a piece of classic mailing list
crypto, where it just sort of sprung up by an anonymous author without a
lot of real analysis of what precisely it was accomplishing. As an ARX
permutation alone, there are some easily searchable differential trails
in it, and as a means of preventing malicious interrupts, it completely
fails, since it xors new data into the entire state every time. It can't
really be analyzed as a random permutation, because it clearly isn't,
and it can't be analyzed as an interesting linear algebraic structure
either, because it's also not that. There really is very little one can
say about it in terms of entropy accumulation. It might diffuse bits,
some of the time, maybe, we hope, I guess. But for the most part, it
fails to accomplish anything concrete.
As a reminder, the simple goal of add_interrupt_randomness() is to
simply accumulate entropy until ~64 interrupts have elapsed, and then
dump it into the main input pool, which uses a cryptographic hash.
It would be nice to have something cryptographically strong in the
interrupt handler itself, in case a malicious interrupt compromises a
per-cpu fast pool within the 64 interrupts / 1 second window, and then
inside of that same window somehow can control its return address and
cycle counter, even if that's a bit far fetched. However, with a very
CPU-limited budget, actually doing that remains an active research
project (and perhaps there'll be something useful for Linux to come out
of it). And while the abundance of caution would be nice, this isn't
*currently* the security model, and we don't yet have a fast enough
solution to make it our security model. Plus there's not exactly a
pressing need to do that. (And for the avoidance of doubt, the actual
cluster of 64 accumulated interrupts still gets dumped into our
cryptographically secure input pool.)
So, for now we are going to stick with the existing interrupt security
model, which assumes that each cluster of 64 interrupt data samples is
mostly non-malicious and not colluding with an infoleaker. With this as
our goal, we have a few more choices, simply aiming to accumulate
entropy, while discarding the least amount of it.
We know from <https://eprint.iacr.org/2019/198> that random oracles,
instantiated as computational hash functions, make good entropy
accumulators and extractors, which is the justification for using
BLAKE2s in the main input pool. As mentioned, we don't have that luxury
here, but we also don't have the same security model requirements,
because we're assuming that there aren't malicious inputs. A
pseudorandom function instance can approximately behave like a random
oracle, provided that the key is uniformly random. But since we're not
concerned with malicious inputs, we can pick a fixed key, which is not
secret, knowing that "nature" won't interact with a sufficiently chosen
fixed key by accident. So we pick a PRF with a fixed initial key, and
accumulate into it continuously, dumping the result every 64 interrupts
into our cryptographically secure input pool.
For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on
32-bit, which are already in use in the kernel's hsiphash family of
functions and achieve the same performance as the function they replace.
It would be nice to do two rounds, but we don't exactly have the CPU
budget handy for that, and one round alone is already sufficient.
As mentioned, we start with a fixed initial key (zeros is fine), and
allow SipHash's symmetry breaking constants to turn that into a useful
starting point. Also, since we're dumping the result (or half of it on
64-bit so as to tax our hash function the same amount on all platforms)
into the cryptographically secure input pool, there's no point in
finalizing SipHash's output, since it'll wind up being finalized by
something much stronger. This means that all we need to do is use the
ordinary round function word-by-word, as normal SipHash does.
Simplified, the flow is as follows:
Initialize:
siphash_state_t state;
siphash_init(&state, key={0, 0, 0, 0});
Update (accumulate) on interrupt:
siphash_update(&state, interrupt_data_and_timing);
Dump into input pool after 64 interrupts:
blake2s_update(&input_pool, &state, sizeof(state) / 2);
The result of all of this is that the security model is unchanged from
before -- we assume non-malicious inputs -- yet we now implement that
model with a stronger argument. I would like to emphasize, again, that
the purpose of this commit is to improve the existing design, by making
it analyzable, without changing any fundamental assumptions. There may
well be value down the road in changing up the existing design, using
something cryptographically strong, or simply using a ring buffer of
samples rather than having a fast_mix() at all, or changing which and
how much data we collect each interrupt so that we can use something
linear, or a variety of other ideas. This commit does not invalidate the
potential for those in the future.
For example, in the future, if we're able to characterize the data we're
collecting on each interrupt, we may be able to inch toward information
theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s
= ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good
accumulators for 2-monotone distributions, which would apply to
timestamp counters, like random_get_entropy() or jiffies, but would not
apply to our current combination of the two values, or to the various
function addresses and register values we mix in. Alternatively,
<https://eprint.iacr.org/2021/1002> shows that max-period linear
functions with no non-trivial invariant subspace make good extractors,
used in the form `s = f(s) ^ x`. However, this only works if the input
data is both identical and independent, and obviously a collection of
address values and counters fails; so it goes with theoretical papers.
Future directions here may involve trying to characterize more precisely
what we actually need to collect in the interrupt handler, and building
something specific around that.
However, as mentioned, the morass of data we're gathering at the
interrupt handler presently defies characterization, and so we use
SipHash for now, which works well and performs well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 14:58:44 +01:00
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2022-05-07 14:03:46 +02:00
|
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|
2022-09-22 18:46:04 +02:00
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|
random: use SipHash as interrupt entropy accumulator
The current fast_mix() function is a piece of classic mailing list
crypto, where it just sort of sprung up by an anonymous author without a
lot of real analysis of what precisely it was accomplishing. As an ARX
permutation alone, there are some easily searchable differential trails
in it, and as a means of preventing malicious interrupts, it completely
fails, since it xors new data into the entire state every time. It can't
really be analyzed as a random permutation, because it clearly isn't,
and it can't be analyzed as an interesting linear algebraic structure
either, because it's also not that. There really is very little one can
say about it in terms of entropy accumulation. It might diffuse bits,
some of the time, maybe, we hope, I guess. But for the most part, it
fails to accomplish anything concrete.
As a reminder, the simple goal of add_interrupt_randomness() is to
simply accumulate entropy until ~64 interrupts have elapsed, and then
dump it into the main input pool, which uses a cryptographic hash.
It would be nice to have something cryptographically strong in the
interrupt handler itself, in case a malicious interrupt compromises a
per-cpu fast pool within the 64 interrupts / 1 second window, and then
inside of that same window somehow can control its return address and
cycle counter, even if that's a bit far fetched. However, with a very
CPU-limited budget, actually doing that remains an active research
project (and perhaps there'll be something useful for Linux to come out
of it). And while the abundance of caution would be nice, this isn't
*currently* the security model, and we don't yet have a fast enough
solution to make it our security model. Plus there's not exactly a
pressing need to do that. (And for the avoidance of doubt, the actual
cluster of 64 accumulated interrupts still gets dumped into our
cryptographically secure input pool.)
So, for now we are going to stick with the existing interrupt security
model, which assumes that each cluster of 64 interrupt data samples is
mostly non-malicious and not colluding with an infoleaker. With this as
our goal, we have a few more choices, simply aiming to accumulate
entropy, while discarding the least amount of it.
We know from <https://eprint.iacr.org/2019/198> that random oracles,
instantiated as computational hash functions, make good entropy
accumulators and extractors, which is the justification for using
BLAKE2s in the main input pool. As mentioned, we don't have that luxury
here, but we also don't have the same security model requirements,
because we're assuming that there aren't malicious inputs. A
pseudorandom function instance can approximately behave like a random
oracle, provided that the key is uniformly random. But since we're not
concerned with malicious inputs, we can pick a fixed key, which is not
secret, knowing that "nature" won't interact with a sufficiently chosen
fixed key by accident. So we pick a PRF with a fixed initial key, and
accumulate into it continuously, dumping the result every 64 interrupts
into our cryptographically secure input pool.
For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on
32-bit, which are already in use in the kernel's hsiphash family of
functions and achieve the same performance as the function they replace.
It would be nice to do two rounds, but we don't exactly have the CPU
budget handy for that, and one round alone is already sufficient.
As mentioned, we start with a fixed initial key (zeros is fine), and
allow SipHash's symmetry breaking constants to turn that into a useful
starting point. Also, since we're dumping the result (or half of it on
64-bit so as to tax our hash function the same amount on all platforms)
into the cryptographically secure input pool, there's no point in
finalizing SipHash's output, since it'll wind up being finalized by
something much stronger. This means that all we need to do is use the
ordinary round function word-by-word, as normal SipHash does.
Simplified, the flow is as follows:
Initialize:
siphash_state_t state;
siphash_init(&state, key={0, 0, 0, 0});
Update (accumulate) on interrupt:
siphash_update(&state, interrupt_data_and_timing);
Dump into input pool after 64 interrupts:
blake2s_update(&input_pool, &state, sizeof(state) / 2);
The result of all of this is that the security model is unchanged from
before -- we assume non-malicious inputs -- yet we now implement that
model with a stronger argument. I would like to emphasize, again, that
the purpose of this commit is to improve the existing design, by making
it analyzable, without changing any fundamental assumptions. There may
well be value down the road in changing up the existing design, using
something cryptographically strong, or simply using a ring buffer of
samples rather than having a fast_mix() at all, or changing which and
how much data we collect each interrupt so that we can use something
linear, or a variety of other ideas. This commit does not invalidate the
potential for those in the future.
For example, in the future, if we're able to characterize the data we're
collecting on each interrupt, we may be able to inch toward information
theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s
= ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good
accumulators for 2-monotone distributions, which would apply to
timestamp counters, like random_get_entropy() or jiffies, but would not
apply to our current combination of the two values, or to the various
function addresses and register values we mix in. Alternatively,
<https://eprint.iacr.org/2021/1002> shows that max-period linear
functions with no non-trivial invariant subspace make good extractors,
used in the form `s = f(s) ^ x`. However, this only works if the input
data is both identical and independent, and obviously a collection of
address values and counters fails; so it goes with theoretical papers.
Future directions here may involve trying to characterize more precisely
what we actually need to collect in the interrupt handler, and building
something specific around that.
However, as mentioned, the morass of data we're gathering at the
interrupt handler presently defies characterization, and so we use
SipHash for now, which works well and performs well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 14:58:44 +01:00
|
|
|
|
2022-05-07 14:03:46 +02:00
|
|
|
|
2022-09-22 18:46:04 +02:00
|
|
|
|
random: use SipHash as interrupt entropy accumulator
The current fast_mix() function is a piece of classic mailing list
crypto, where it just sort of sprung up by an anonymous author without a
lot of real analysis of what precisely it was accomplishing. As an ARX
permutation alone, there are some easily searchable differential trails
in it, and as a means of preventing malicious interrupts, it completely
fails, since it xors new data into the entire state every time. It can't
really be analyzed as a random permutation, because it clearly isn't,
and it can't be analyzed as an interesting linear algebraic structure
either, because it's also not that. There really is very little one can
say about it in terms of entropy accumulation. It might diffuse bits,
some of the time, maybe, we hope, I guess. But for the most part, it
fails to accomplish anything concrete.
As a reminder, the simple goal of add_interrupt_randomness() is to
simply accumulate entropy until ~64 interrupts have elapsed, and then
dump it into the main input pool, which uses a cryptographic hash.
It would be nice to have something cryptographically strong in the
interrupt handler itself, in case a malicious interrupt compromises a
per-cpu fast pool within the 64 interrupts / 1 second window, and then
inside of that same window somehow can control its return address and
cycle counter, even if that's a bit far fetched. However, with a very
CPU-limited budget, actually doing that remains an active research
project (and perhaps there'll be something useful for Linux to come out
of it). And while the abundance of caution would be nice, this isn't
*currently* the security model, and we don't yet have a fast enough
solution to make it our security model. Plus there's not exactly a
pressing need to do that. (And for the avoidance of doubt, the actual
cluster of 64 accumulated interrupts still gets dumped into our
cryptographically secure input pool.)
So, for now we are going to stick with the existing interrupt security
model, which assumes that each cluster of 64 interrupt data samples is
mostly non-malicious and not colluding with an infoleaker. With this as
our goal, we have a few more choices, simply aiming to accumulate
entropy, while discarding the least amount of it.
We know from <https://eprint.iacr.org/2019/198> that random oracles,
instantiated as computational hash functions, make good entropy
accumulators and extractors, which is the justification for using
BLAKE2s in the main input pool. As mentioned, we don't have that luxury
here, but we also don't have the same security model requirements,
because we're assuming that there aren't malicious inputs. A
pseudorandom function instance can approximately behave like a random
oracle, provided that the key is uniformly random. But since we're not
concerned with malicious inputs, we can pick a fixed key, which is not
secret, knowing that "nature" won't interact with a sufficiently chosen
fixed key by accident. So we pick a PRF with a fixed initial key, and
accumulate into it continuously, dumping the result every 64 interrupts
into our cryptographically secure input pool.
For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on
32-bit, which are already in use in the kernel's hsiphash family of
functions and achieve the same performance as the function they replace.
It would be nice to do two rounds, but we don't exactly have the CPU
budget handy for that, and one round alone is already sufficient.
As mentioned, we start with a fixed initial key (zeros is fine), and
allow SipHash's symmetry breaking constants to turn that into a useful
starting point. Also, since we're dumping the result (or half of it on
64-bit so as to tax our hash function the same amount on all platforms)
into the cryptographically secure input pool, there's no point in
finalizing SipHash's output, since it'll wind up being finalized by
something much stronger. This means that all we need to do is use the
ordinary round function word-by-word, as normal SipHash does.
Simplified, the flow is as follows:
Initialize:
siphash_state_t state;
siphash_init(&state, key={0, 0, 0, 0});
Update (accumulate) on interrupt:
siphash_update(&state, interrupt_data_and_timing);
Dump into input pool after 64 interrupts:
blake2s_update(&input_pool, &state, sizeof(state) / 2);
The result of all of this is that the security model is unchanged from
before -- we assume non-malicious inputs -- yet we now implement that
model with a stronger argument. I would like to emphasize, again, that
the purpose of this commit is to improve the existing design, by making
it analyzable, without changing any fundamental assumptions. There may
well be value down the road in changing up the existing design, using
something cryptographically strong, or simply using a ring buffer of
samples rather than having a fast_mix() at all, or changing which and
how much data we collect each interrupt so that we can use something
linear, or a variety of other ideas. This commit does not invalidate the
potential for those in the future.
For example, in the future, if we're able to characterize the data we're
collecting on each interrupt, we may be able to inch toward information
theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s
= ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good
accumulators for 2-monotone distributions, which would apply to
timestamp counters, like random_get_entropy() or jiffies, but would not
apply to our current combination of the two values, or to the various
function addresses and register values we mix in. Alternatively,
<https://eprint.iacr.org/2021/1002> shows that max-period linear
functions with no non-trivial invariant subspace make good extractors,
used in the form `s = f(s) ^ x`. However, this only works if the input
data is both identical and independent, and obviously a collection of
address values and counters fails; so it goes with theoretical papers.
Future directions here may involve trying to characterize more precisely
what we actually need to collect in the interrupt handler, and building
something specific around that.
However, as mentioned, the morass of data we're gathering at the
interrupt handler presently defies characterization, and so we use
SipHash for now, which works well and performs well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 14:58:44 +01:00
|
|
|
|
2022-09-22 18:46:04 +02:00
|
|
|
|
random: use SipHash as interrupt entropy accumulator
The current fast_mix() function is a piece of classic mailing list
crypto, where it just sort of sprung up by an anonymous author without a
lot of real analysis of what precisely it was accomplishing. As an ARX
permutation alone, there are some easily searchable differential trails
in it, and as a means of preventing malicious interrupts, it completely
fails, since it xors new data into the entire state every time. It can't
really be analyzed as a random permutation, because it clearly isn't,
and it can't be analyzed as an interesting linear algebraic structure
either, because it's also not that. There really is very little one can
say about it in terms of entropy accumulation. It might diffuse bits,
some of the time, maybe, we hope, I guess. But for the most part, it
fails to accomplish anything concrete.
As a reminder, the simple goal of add_interrupt_randomness() is to
simply accumulate entropy until ~64 interrupts have elapsed, and then
dump it into the main input pool, which uses a cryptographic hash.
It would be nice to have something cryptographically strong in the
interrupt handler itself, in case a malicious interrupt compromises a
per-cpu fast pool within the 64 interrupts / 1 second window, and then
inside of that same window somehow can control its return address and
cycle counter, even if that's a bit far fetched. However, with a very
CPU-limited budget, actually doing that remains an active research
project (and perhaps there'll be something useful for Linux to come out
of it). And while the abundance of caution would be nice, this isn't
*currently* the security model, and we don't yet have a fast enough
solution to make it our security model. Plus there's not exactly a
pressing need to do that. (And for the avoidance of doubt, the actual
cluster of 64 accumulated interrupts still gets dumped into our
cryptographically secure input pool.)
So, for now we are going to stick with the existing interrupt security
model, which assumes that each cluster of 64 interrupt data samples is
mostly non-malicious and not colluding with an infoleaker. With this as
our goal, we have a few more choices, simply aiming to accumulate
entropy, while discarding the least amount of it.
We know from <https://eprint.iacr.org/2019/198> that random oracles,
instantiated as computational hash functions, make good entropy
accumulators and extractors, which is the justification for using
BLAKE2s in the main input pool. As mentioned, we don't have that luxury
here, but we also don't have the same security model requirements,
because we're assuming that there aren't malicious inputs. A
pseudorandom function instance can approximately behave like a random
oracle, provided that the key is uniformly random. But since we're not
concerned with malicious inputs, we can pick a fixed key, which is not
secret, knowing that "nature" won't interact with a sufficiently chosen
fixed key by accident. So we pick a PRF with a fixed initial key, and
accumulate into it continuously, dumping the result every 64 interrupts
into our cryptographically secure input pool.
For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on
32-bit, which are already in use in the kernel's hsiphash family of
functions and achieve the same performance as the function they replace.
It would be nice to do two rounds, but we don't exactly have the CPU
budget handy for that, and one round alone is already sufficient.
As mentioned, we start with a fixed initial key (zeros is fine), and
allow SipHash's symmetry breaking constants to turn that into a useful
starting point. Also, since we're dumping the result (or half of it on
64-bit so as to tax our hash function the same amount on all platforms)
into the cryptographically secure input pool, there's no point in
finalizing SipHash's output, since it'll wind up being finalized by
something much stronger. This means that all we need to do is use the
ordinary round function word-by-word, as normal SipHash does.
Simplified, the flow is as follows:
Initialize:
siphash_state_t state;
siphash_init(&state, key={0, 0, 0, 0});
Update (accumulate) on interrupt:
siphash_update(&state, interrupt_data_and_timing);
Dump into input pool after 64 interrupts:
blake2s_update(&input_pool, &state, sizeof(state) / 2);
The result of all of this is that the security model is unchanged from
before -- we assume non-malicious inputs -- yet we now implement that
model with a stronger argument. I would like to emphasize, again, that
the purpose of this commit is to improve the existing design, by making
it analyzable, without changing any fundamental assumptions. There may
well be value down the road in changing up the existing design, using
something cryptographically strong, or simply using a ring buffer of
samples rather than having a fast_mix() at all, or changing which and
how much data we collect each interrupt so that we can use something
linear, or a variety of other ideas. This commit does not invalidate the
potential for those in the future.
For example, in the future, if we're able to characterize the data we're
collecting on each interrupt, we may be able to inch toward information
theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s
= ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good
accumulators for 2-monotone distributions, which would apply to
timestamp counters, like random_get_entropy() or jiffies, but would not
apply to our current combination of the two values, or to the various
function addresses and register values we mix in. Alternatively,
<https://eprint.iacr.org/2021/1002> shows that max-period linear
functions with no non-trivial invariant subspace make good extractors,
used in the form `s = f(s) ^ x`. However, this only works if the input
data is both identical and independent, and obviously a collection of
address values and counters fails; so it goes with theoretical papers.
Future directions here may involve trying to characterize more precisely
what we actually need to collect in the interrupt handler, and building
something specific around that.
However, as mentioned, the morass of data we're gathering at the
interrupt handler presently defies characterization, and so we use
SipHash for now, which works well and performs well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 14:58:44 +01:00
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2022-02-11 12:53:34 +01:00
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random: use SipHash as interrupt entropy accumulator
The current fast_mix() function is a piece of classic mailing list
crypto, where it just sort of sprung up by an anonymous author without a
lot of real analysis of what precisely it was accomplishing. As an ARX
permutation alone, there are some easily searchable differential trails
in it, and as a means of preventing malicious interrupts, it completely
fails, since it xors new data into the entire state every time. It can't
really be analyzed as a random permutation, because it clearly isn't,
and it can't be analyzed as an interesting linear algebraic structure
either, because it's also not that. There really is very little one can
say about it in terms of entropy accumulation. It might diffuse bits,
some of the time, maybe, we hope, I guess. But for the most part, it
fails to accomplish anything concrete.
As a reminder, the simple goal of add_interrupt_randomness() is to
simply accumulate entropy until ~64 interrupts have elapsed, and then
dump it into the main input pool, which uses a cryptographic hash.
It would be nice to have something cryptographically strong in the
interrupt handler itself, in case a malicious interrupt compromises a
per-cpu fast pool within the 64 interrupts / 1 second window, and then
inside of that same window somehow can control its return address and
cycle counter, even if that's a bit far fetched. However, with a very
CPU-limited budget, actually doing that remains an active research
project (and perhaps there'll be something useful for Linux to come out
of it). And while the abundance of caution would be nice, this isn't
*currently* the security model, and we don't yet have a fast enough
solution to make it our security model. Plus there's not exactly a
pressing need to do that. (And for the avoidance of doubt, the actual
cluster of 64 accumulated interrupts still gets dumped into our
cryptographically secure input pool.)
So, for now we are going to stick with the existing interrupt security
model, which assumes that each cluster of 64 interrupt data samples is
mostly non-malicious and not colluding with an infoleaker. With this as
our goal, we have a few more choices, simply aiming to accumulate
entropy, while discarding the least amount of it.
We know from <https://eprint.iacr.org/2019/198> that random oracles,
instantiated as computational hash functions, make good entropy
accumulators and extractors, which is the justification for using
BLAKE2s in the main input pool. As mentioned, we don't have that luxury
here, but we also don't have the same security model requirements,
because we're assuming that there aren't malicious inputs. A
pseudorandom function instance can approximately behave like a random
oracle, provided that the key is uniformly random. But since we're not
concerned with malicious inputs, we can pick a fixed key, which is not
secret, knowing that "nature" won't interact with a sufficiently chosen
fixed key by accident. So we pick a PRF with a fixed initial key, and
accumulate into it continuously, dumping the result every 64 interrupts
into our cryptographically secure input pool.
For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on
32-bit, which are already in use in the kernel's hsiphash family of
functions and achieve the same performance as the function they replace.
It would be nice to do two rounds, but we don't exactly have the CPU
budget handy for that, and one round alone is already sufficient.
As mentioned, we start with a fixed initial key (zeros is fine), and
allow SipHash's symmetry breaking constants to turn that into a useful
starting point. Also, since we're dumping the result (or half of it on
64-bit so as to tax our hash function the same amount on all platforms)
into the cryptographically secure input pool, there's no point in
finalizing SipHash's output, since it'll wind up being finalized by
something much stronger. This means that all we need to do is use the
ordinary round function word-by-word, as normal SipHash does.
Simplified, the flow is as follows:
Initialize:
siphash_state_t state;
siphash_init(&state, key={0, 0, 0, 0});
Update (accumulate) on interrupt:
siphash_update(&state, interrupt_data_and_timing);
Dump into input pool after 64 interrupts:
blake2s_update(&input_pool, &state, sizeof(state) / 2);
The result of all of this is that the security model is unchanged from
before -- we assume non-malicious inputs -- yet we now implement that
model with a stronger argument. I would like to emphasize, again, that
the purpose of this commit is to improve the existing design, by making
it analyzable, without changing any fundamental assumptions. There may
well be value down the road in changing up the existing design, using
something cryptographically strong, or simply using a ring buffer of
samples rather than having a fast_mix() at all, or changing which and
how much data we collect each interrupt so that we can use something
linear, or a variety of other ideas. This commit does not invalidate the
potential for those in the future.
For example, in the future, if we're able to characterize the data we're
collecting on each interrupt, we may be able to inch toward information
theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s
= ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good
accumulators for 2-monotone distributions, which would apply to
timestamp counters, like random_get_entropy() or jiffies, but would not
apply to our current combination of the two values, or to the various
function addresses and register values we mix in. Alternatively,
<https://eprint.iacr.org/2021/1002> shows that max-period linear
functions with no non-trivial invariant subspace make good extractors,
used in the form `s = f(s) ^ x`. However, this only works if the input
data is both identical and independent, and obviously a collection of
address values and counters fails; so it goes with theoretical papers.
Future directions here may involve trying to characterize more precisely
what we actually need to collect in the interrupt handler, and building
something specific around that.
However, as mentioned, the morass of data we're gathering at the
interrupt handler presently defies characterization, and so we use
SipHash for now, which works well and performs well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 14:58:44 +01:00
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random: insist on random_get_entropy() existing in order to simplify
All platforms are now guaranteed to provide some value for
random_get_entropy(). In case some bug leads to this not being so, we
print a warning, because that indicates that something is really very
wrong (and likely other things are impacted too). This should never be
hit, but it's a good and cheap way of finding out if something ever is
problematic.
Since we now have viable fallback code for random_get_entropy() on all
platforms, which is, in the worst case, not worse than jiffies, we can
count on getting the best possible value out of it. That means there's
no longer a use for using jiffies as entropy input. It also means we no
longer have a reason for doing the round-robin register flow in the IRQ
handler, which was always of fairly dubious value.
Instead we can greatly simplify the IRQ handler inputs and also unify
the construction between 64-bits and 32-bits. We now collect the cycle
counter and the return address, since those are the two things that
matter. Because the return address and the irq number are likely
related, to the extent we mix in the irq number, we can just xor it into
the top unchanging bytes of the return address, rather than the bottom
changing bytes of the cycle counter as before. Then, we can do a fixed 2
rounds of SipHash/HSipHash. Finally, we use the same construction of
hashing only half of the [H]SipHash state on 32-bit and 64-bit. We're
not actually discarding any entropy, since that entropy is carried
through until the next time. And more importantly, it lets us do the
same sponge-like construction everywhere.
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-12 19:59:57 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-06 23:19:43 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-06 23:19:43 +02:00
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2022-05-07 14:03:46 +02:00
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2022-05-06 23:19:43 +02:00
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2022-05-07 14:03:46 +02:00
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2022-05-06 23:19:43 +02:00
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2022-02-11 12:53:34 +01:00
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random: clear fast pool, crng, and batches in cpuhp bring up
For the irq randomness fast pool, rather than having to use expensive
atomics, which were visibly the most expensive thing in the entire irq
handler, simply take care of the extreme edge case of resetting count to
zero in the cpuhp online handler, just after workqueues have been
reenabled. This simplifies the code a bit and lets us use vanilla
variables rather than atomics, and performance should be improved.
As well, very early on when the CPU comes up, while interrupts are still
disabled, we clear out the per-cpu crng and its batches, so that it
always starts with fresh randomness.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-13 22:48:04 +01:00
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2022-05-13 16:17:12 +02:00
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random: clear fast pool, crng, and batches in cpuhp bring up
For the irq randomness fast pool, rather than having to use expensive
atomics, which were visibly the most expensive thing in the entire irq
handler, simply take care of the extreme edge case of resetting count to
zero in the cpuhp online handler, just after workqueues have been
reenabled. This simplifies the code a bit and lets us use vanilla
variables rather than atomics, and performance should be improved.
As well, very early on when the CPU comes up, while interrupts are still
disabled, we clear out the per-cpu crng and its batches, so that it
always starts with fresh randomness.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-13 22:48:04 +01:00
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2022-09-22 18:46:04 +02:00
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random: defer fast pool mixing to worker
On PREEMPT_RT, it's problematic to take spinlocks from hard irq
handlers. We can fix this by deferring to a workqueue the dumping of
the fast pool into the input pool.
We accomplish this with some careful rules on fast_pool->count:
- When it's incremented to >= 64, we schedule the work.
- If the top bit is set, we never schedule the work, even if >= 64.
- The worker is responsible for setting it back to 0 when it's done.
There are two small issues around using workqueues for this purpose that
we work around.
The first issue is that mix_interrupt_randomness() might be migrated to
another CPU during CPU hotplug. This issue is rectified by checking that
it hasn't been migrated (after disabling irqs). If it has been migrated,
then we set the count to zero, so that when the CPU comes online again,
it can requeue the work. As part of this, we switch to using an
atomic_t, so that the increment in the irq handler doesn't wipe out the
zeroing if the CPU comes back online while this worker is running.
The second issue is that, though relatively minor in effect, we probably
want to make sure we get a consistent view of the pool onto the stack,
in case it's interrupted by an irq while reading. To do this, we don't
reenable irqs until after the copy. There are only 18 instructions
between the cli and sti, so this is a pretty tiny window.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 16:15:46 +01:00
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random: use SipHash as interrupt entropy accumulator
The current fast_mix() function is a piece of classic mailing list
crypto, where it just sort of sprung up by an anonymous author without a
lot of real analysis of what precisely it was accomplishing. As an ARX
permutation alone, there are some easily searchable differential trails
in it, and as a means of preventing malicious interrupts, it completely
fails, since it xors new data into the entire state every time. It can't
really be analyzed as a random permutation, because it clearly isn't,
and it can't be analyzed as an interesting linear algebraic structure
either, because it's also not that. There really is very little one can
say about it in terms of entropy accumulation. It might diffuse bits,
some of the time, maybe, we hope, I guess. But for the most part, it
fails to accomplish anything concrete.
As a reminder, the simple goal of add_interrupt_randomness() is to
simply accumulate entropy until ~64 interrupts have elapsed, and then
dump it into the main input pool, which uses a cryptographic hash.
It would be nice to have something cryptographically strong in the
interrupt handler itself, in case a malicious interrupt compromises a
per-cpu fast pool within the 64 interrupts / 1 second window, and then
inside of that same window somehow can control its return address and
cycle counter, even if that's a bit far fetched. However, with a very
CPU-limited budget, actually doing that remains an active research
project (and perhaps there'll be something useful for Linux to come out
of it). And while the abundance of caution would be nice, this isn't
*currently* the security model, and we don't yet have a fast enough
solution to make it our security model. Plus there's not exactly a
pressing need to do that. (And for the avoidance of doubt, the actual
cluster of 64 accumulated interrupts still gets dumped into our
cryptographically secure input pool.)
So, for now we are going to stick with the existing interrupt security
model, which assumes that each cluster of 64 interrupt data samples is
mostly non-malicious and not colluding with an infoleaker. With this as
our goal, we have a few more choices, simply aiming to accumulate
entropy, while discarding the least amount of it.
We know from <https://eprint.iacr.org/2019/198> that random oracles,
instantiated as computational hash functions, make good entropy
accumulators and extractors, which is the justification for using
BLAKE2s in the main input pool. As mentioned, we don't have that luxury
here, but we also don't have the same security model requirements,
because we're assuming that there aren't malicious inputs. A
pseudorandom function instance can approximately behave like a random
oracle, provided that the key is uniformly random. But since we're not
concerned with malicious inputs, we can pick a fixed key, which is not
secret, knowing that "nature" won't interact with a sufficiently chosen
fixed key by accident. So we pick a PRF with a fixed initial key, and
accumulate into it continuously, dumping the result every 64 interrupts
into our cryptographically secure input pool.
For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on
32-bit, which are already in use in the kernel's hsiphash family of
functions and achieve the same performance as the function they replace.
It would be nice to do two rounds, but we don't exactly have the CPU
budget handy for that, and one round alone is already sufficient.
As mentioned, we start with a fixed initial key (zeros is fine), and
allow SipHash's symmetry breaking constants to turn that into a useful
starting point. Also, since we're dumping the result (or half of it on
64-bit so as to tax our hash function the same amount on all platforms)
into the cryptographically secure input pool, there's no point in
finalizing SipHash's output, since it'll wind up being finalized by
something much stronger. This means that all we need to do is use the
ordinary round function word-by-word, as normal SipHash does.
Simplified, the flow is as follows:
Initialize:
siphash_state_t state;
siphash_init(&state, key={0, 0, 0, 0});
Update (accumulate) on interrupt:
siphash_update(&state, interrupt_data_and_timing);
Dump into input pool after 64 interrupts:
blake2s_update(&input_pool, &state, sizeof(state) / 2);
The result of all of this is that the security model is unchanged from
before -- we assume non-malicious inputs -- yet we now implement that
model with a stronger argument. I would like to emphasize, again, that
the purpose of this commit is to improve the existing design, by making
it analyzable, without changing any fundamental assumptions. There may
well be value down the road in changing up the existing design, using
something cryptographically strong, or simply using a ring buffer of
samples rather than having a fast_mix() at all, or changing which and
how much data we collect each interrupt so that we can use something
linear, or a variety of other ideas. This commit does not invalidate the
potential for those in the future.
For example, in the future, if we're able to characterize the data we're
collecting on each interrupt, we may be able to inch toward information
theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s
= ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good
accumulators for 2-monotone distributions, which would apply to
timestamp counters, like random_get_entropy() or jiffies, but would not
apply to our current combination of the two values, or to the various
function addresses and register values we mix in. Alternatively,
<https://eprint.iacr.org/2021/1002> shows that max-period linear
functions with no non-trivial invariant subspace make good extractors,
used in the form `s = f(s) ^ x`. However, this only works if the input
data is both identical and independent, and obviously a collection of
address values and counters fails; so it goes with theoretical papers.
Future directions here may involve trying to characterize more precisely
what we actually need to collect in the interrupt handler, and building
something specific around that.
However, as mentioned, the morass of data we're gathering at the
interrupt handler presently defies characterization, and so we use
SipHash for now, which works well and performs well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 14:58:44 +01:00
|
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|
random: insist on random_get_entropy() existing in order to simplify
All platforms are now guaranteed to provide some value for
random_get_entropy(). In case some bug leads to this not being so, we
print a warning, because that indicates that something is really very
wrong (and likely other things are impacted too). This should never be
hit, but it's a good and cheap way of finding out if something ever is
problematic.
Since we now have viable fallback code for random_get_entropy() on all
platforms, which is, in the worst case, not worse than jiffies, we can
count on getting the best possible value out of it. That means there's
no longer a use for using jiffies as entropy input. It also means we no
longer have a reason for doing the round-robin register flow in the IRQ
handler, which was always of fairly dubious value.
Instead we can greatly simplify the IRQ handler inputs and also unify
the construction between 64-bits and 32-bits. We now collect the cycle
counter and the return address, since those are the two things that
matter. Because the return address and the irq number are likely
related, to the extent we mix in the irq number, we can just xor it into
the top unchanging bytes of the return address, rather than the bottom
changing bytes of the cycle counter as before. Then, we can do a fixed 2
rounds of SipHash/HSipHash. Finally, we use the same construction of
hashing only half of the [H]SipHash state on 32-bit and 64-bit. We're
not actually discarding any entropy, since that entropy is carried
through until the next time. And more importantly, it lets us do the
same sponge-like construction everywhere.
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-12 19:59:57 +02:00
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random: use SipHash as interrupt entropy accumulator
The current fast_mix() function is a piece of classic mailing list
crypto, where it just sort of sprung up by an anonymous author without a
lot of real analysis of what precisely it was accomplishing. As an ARX
permutation alone, there are some easily searchable differential trails
in it, and as a means of preventing malicious interrupts, it completely
fails, since it xors new data into the entire state every time. It can't
really be analyzed as a random permutation, because it clearly isn't,
and it can't be analyzed as an interesting linear algebraic structure
either, because it's also not that. There really is very little one can
say about it in terms of entropy accumulation. It might diffuse bits,
some of the time, maybe, we hope, I guess. But for the most part, it
fails to accomplish anything concrete.
As a reminder, the simple goal of add_interrupt_randomness() is to
simply accumulate entropy until ~64 interrupts have elapsed, and then
dump it into the main input pool, which uses a cryptographic hash.
It would be nice to have something cryptographically strong in the
interrupt handler itself, in case a malicious interrupt compromises a
per-cpu fast pool within the 64 interrupts / 1 second window, and then
inside of that same window somehow can control its return address and
cycle counter, even if that's a bit far fetched. However, with a very
CPU-limited budget, actually doing that remains an active research
project (and perhaps there'll be something useful for Linux to come out
of it). And while the abundance of caution would be nice, this isn't
*currently* the security model, and we don't yet have a fast enough
solution to make it our security model. Plus there's not exactly a
pressing need to do that. (And for the avoidance of doubt, the actual
cluster of 64 accumulated interrupts still gets dumped into our
cryptographically secure input pool.)
So, for now we are going to stick with the existing interrupt security
model, which assumes that each cluster of 64 interrupt data samples is
mostly non-malicious and not colluding with an infoleaker. With this as
our goal, we have a few more choices, simply aiming to accumulate
entropy, while discarding the least amount of it.
We know from <https://eprint.iacr.org/2019/198> that random oracles,
instantiated as computational hash functions, make good entropy
accumulators and extractors, which is the justification for using
BLAKE2s in the main input pool. As mentioned, we don't have that luxury
here, but we also don't have the same security model requirements,
because we're assuming that there aren't malicious inputs. A
pseudorandom function instance can approximately behave like a random
oracle, provided that the key is uniformly random. But since we're not
concerned with malicious inputs, we can pick a fixed key, which is not
secret, knowing that "nature" won't interact with a sufficiently chosen
fixed key by accident. So we pick a PRF with a fixed initial key, and
accumulate into it continuously, dumping the result every 64 interrupts
into our cryptographically secure input pool.
For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on
32-bit, which are already in use in the kernel's hsiphash family of
functions and achieve the same performance as the function they replace.
It would be nice to do two rounds, but we don't exactly have the CPU
budget handy for that, and one round alone is already sufficient.
As mentioned, we start with a fixed initial key (zeros is fine), and
allow SipHash's symmetry breaking constants to turn that into a useful
starting point. Also, since we're dumping the result (or half of it on
64-bit so as to tax our hash function the same amount on all platforms)
into the cryptographically secure input pool, there's no point in
finalizing SipHash's output, since it'll wind up being finalized by
something much stronger. This means that all we need to do is use the
ordinary round function word-by-word, as normal SipHash does.
Simplified, the flow is as follows:
Initialize:
siphash_state_t state;
siphash_init(&state, key={0, 0, 0, 0});
Update (accumulate) on interrupt:
siphash_update(&state, interrupt_data_and_timing);
Dump into input pool after 64 interrupts:
blake2s_update(&input_pool, &state, sizeof(state) / 2);
The result of all of this is that the security model is unchanged from
before -- we assume non-malicious inputs -- yet we now implement that
model with a stronger argument. I would like to emphasize, again, that
the purpose of this commit is to improve the existing design, by making
it analyzable, without changing any fundamental assumptions. There may
well be value down the road in changing up the existing design, using
something cryptographically strong, or simply using a ring buffer of
samples rather than having a fast_mix() at all, or changing which and
how much data we collect each interrupt so that we can use something
linear, or a variety of other ideas. This commit does not invalidate the
potential for those in the future.
For example, in the future, if we're able to characterize the data we're
collecting on each interrupt, we may be able to inch toward information
theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s
= ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good
accumulators for 2-monotone distributions, which would apply to
timestamp counters, like random_get_entropy() or jiffies, but would not
apply to our current combination of the two values, or to the various
function addresses and register values we mix in. Alternatively,
<https://eprint.iacr.org/2021/1002> shows that max-period linear
functions with no non-trivial invariant subspace make good extractors,
used in the form `s = f(s) ^ x`. However, this only works if the input
data is both identical and independent, and obviously a collection of
address values and counters fails; so it goes with theoretical papers.
Future directions here may involve trying to characterize more precisely
what we actually need to collect in the interrupt handler, and building
something specific around that.
However, as mentioned, the morass of data we're gathering at the
interrupt handler presently defies characterization, and so we use
SipHash for now, which works well and performs well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 14:58:44 +01:00
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random: insist on random_get_entropy() existing in order to simplify
All platforms are now guaranteed to provide some value for
random_get_entropy(). In case some bug leads to this not being so, we
print a warning, because that indicates that something is really very
wrong (and likely other things are impacted too). This should never be
hit, but it's a good and cheap way of finding out if something ever is
problematic.
Since we now have viable fallback code for random_get_entropy() on all
platforms, which is, in the worst case, not worse than jiffies, we can
count on getting the best possible value out of it. That means there's
no longer a use for using jiffies as entropy input. It also means we no
longer have a reason for doing the round-robin register flow in the IRQ
handler, which was always of fairly dubious value.
Instead we can greatly simplify the IRQ handler inputs and also unify
the construction between 64-bits and 32-bits. We now collect the cycle
counter and the return address, since those are the two things that
matter. Because the return address and the irq number are likely
related, to the extent we mix in the irq number, we can just xor it into
the top unchanging bytes of the return address, rather than the bottom
changing bytes of the cycle counter as before. Then, we can do a fixed 2
rounds of SipHash/HSipHash. Finally, we use the same construction of
hashing only half of the [H]SipHash state on 32-bit and 64-bit. We're
not actually discarding any entropy, since that entropy is carried
through until the next time. And more importantly, it lets us do the
same sponge-like construction everywhere.
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-12 19:59:57 +02:00
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random: do not use input pool from hard IRQs
Years ago, a separate fast pool was added for interrupts, so that the
cost associated with taking the input pool spinlocks and mixing into it
would be avoided in places where latency is critical. However, one
oversight was that add_input_randomness() and add_disk_randomness()
still sometimes are called directly from the interrupt handler, rather
than being deferred to a thread. This means that some unlucky interrupts
will be caught doing a blake2s_compress() call and potentially spinning
on input_pool.lock, which can also be taken by unprivileged users by
writing into /dev/urandom.
In order to fix this, add_timer_randomness() now checks whether it is
being called from a hard IRQ and if so, just mixes into the per-cpu IRQ
fast pool using fast_mix(), which is much faster and can be done
lock-free. A nice consequence of this, as well, is that it means hard
IRQ context FPU support is likely no longer useful.
The entropy estimation algorithm used by add_timer_randomness() is also
somewhat different than the one used for add_interrupt_randomness(). The
former looks at deltas of deltas of deltas, while the latter just waits
for 64 interrupts for one bit or for one second since the last bit. In
order to bridge these, and since add_interrupt_randomness() runs after
an add_timer_randomness() that's called from hard IRQ, we add to the
fast pool credit the related amount, and then subtract one to account
for add_interrupt_randomness()'s contribution.
A downside of this, however, is that the num argument is potentially
attacker controlled, which puts a bit more pressure on the fast_mix()
sponge to do more than it's really intended to do. As a mitigating
factor, the first 96 bits of input aren't attacker controlled (a cycle
counter followed by zeros), which means it's essentially two rounds of
siphash rather than one, which is somewhat better. It's also not that
much different from add_interrupt_randomness()'s use of the irq stack
instruction pointer register.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Filipe Manana <fdmanana@suse.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Borislav Petkov <bp@alien8.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-06 18:30:51 +02:00
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random: defer fast pool mixing to worker
On PREEMPT_RT, it's problematic to take spinlocks from hard irq
handlers. We can fix this by deferring to a workqueue the dumping of
the fast pool into the input pool.
We accomplish this with some careful rules on fast_pool->count:
- When it's incremented to >= 64, we schedule the work.
- If the top bit is set, we never schedule the work, even if >= 64.
- The worker is responsible for setting it back to 0 when it's done.
There are two small issues around using workqueues for this purpose that
we work around.
The first issue is that mix_interrupt_randomness() might be migrated to
another CPU during CPU hotplug. This issue is rectified by checking that
it hasn't been migrated (after disabling irqs). If it has been migrated,
then we set the count to zero, so that when the CPU comes online again,
it can requeue the work. As part of this, we switch to using an
atomic_t, so that the increment in the irq handler doesn't wipe out the
zeroing if the CPU comes back online while this worker is running.
The second issue is that, though relatively minor in effect, we probably
want to make sure we get a consistent view of the pool onto the stack,
in case it's interrupted by an irq while reading. To do this, we don't
reenable irqs until after the copy. There are only 18 instructions
between the cli and sti, so this is a pretty tiny window.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 16:15:46 +01:00
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random: use SipHash as interrupt entropy accumulator
The current fast_mix() function is a piece of classic mailing list
crypto, where it just sort of sprung up by an anonymous author without a
lot of real analysis of what precisely it was accomplishing. As an ARX
permutation alone, there are some easily searchable differential trails
in it, and as a means of preventing malicious interrupts, it completely
fails, since it xors new data into the entire state every time. It can't
really be analyzed as a random permutation, because it clearly isn't,
and it can't be analyzed as an interesting linear algebraic structure
either, because it's also not that. There really is very little one can
say about it in terms of entropy accumulation. It might diffuse bits,
some of the time, maybe, we hope, I guess. But for the most part, it
fails to accomplish anything concrete.
As a reminder, the simple goal of add_interrupt_randomness() is to
simply accumulate entropy until ~64 interrupts have elapsed, and then
dump it into the main input pool, which uses a cryptographic hash.
It would be nice to have something cryptographically strong in the
interrupt handler itself, in case a malicious interrupt compromises a
per-cpu fast pool within the 64 interrupts / 1 second window, and then
inside of that same window somehow can control its return address and
cycle counter, even if that's a bit far fetched. However, with a very
CPU-limited budget, actually doing that remains an active research
project (and perhaps there'll be something useful for Linux to come out
of it). And while the abundance of caution would be nice, this isn't
*currently* the security model, and we don't yet have a fast enough
solution to make it our security model. Plus there's not exactly a
pressing need to do that. (And for the avoidance of doubt, the actual
cluster of 64 accumulated interrupts still gets dumped into our
cryptographically secure input pool.)
So, for now we are going to stick with the existing interrupt security
model, which assumes that each cluster of 64 interrupt data samples is
mostly non-malicious and not colluding with an infoleaker. With this as
our goal, we have a few more choices, simply aiming to accumulate
entropy, while discarding the least amount of it.
We know from <https://eprint.iacr.org/2019/198> that random oracles,
instantiated as computational hash functions, make good entropy
accumulators and extractors, which is the justification for using
BLAKE2s in the main input pool. As mentioned, we don't have that luxury
here, but we also don't have the same security model requirements,
because we're assuming that there aren't malicious inputs. A
pseudorandom function instance can approximately behave like a random
oracle, provided that the key is uniformly random. But since we're not
concerned with malicious inputs, we can pick a fixed key, which is not
secret, knowing that "nature" won't interact with a sufficiently chosen
fixed key by accident. So we pick a PRF with a fixed initial key, and
accumulate into it continuously, dumping the result every 64 interrupts
into our cryptographically secure input pool.
For this, we make use of SipHash-1-x on 64-bit and HalfSipHash-1-x on
32-bit, which are already in use in the kernel's hsiphash family of
functions and achieve the same performance as the function they replace.
It would be nice to do two rounds, but we don't exactly have the CPU
budget handy for that, and one round alone is already sufficient.
As mentioned, we start with a fixed initial key (zeros is fine), and
allow SipHash's symmetry breaking constants to turn that into a useful
starting point. Also, since we're dumping the result (or half of it on
64-bit so as to tax our hash function the same amount on all platforms)
into the cryptographically secure input pool, there's no point in
finalizing SipHash's output, since it'll wind up being finalized by
something much stronger. This means that all we need to do is use the
ordinary round function word-by-word, as normal SipHash does.
Simplified, the flow is as follows:
Initialize:
siphash_state_t state;
siphash_init(&state, key={0, 0, 0, 0});
Update (accumulate) on interrupt:
siphash_update(&state, interrupt_data_and_timing);
Dump into input pool after 64 interrupts:
blake2s_update(&input_pool, &state, sizeof(state) / 2);
The result of all of this is that the security model is unchanged from
before -- we assume non-malicious inputs -- yet we now implement that
model with a stronger argument. I would like to emphasize, again, that
the purpose of this commit is to improve the existing design, by making
it analyzable, without changing any fundamental assumptions. There may
well be value down the road in changing up the existing design, using
something cryptographically strong, or simply using a ring buffer of
samples rather than having a fast_mix() at all, or changing which and
how much data we collect each interrupt so that we can use something
linear, or a variety of other ideas. This commit does not invalidate the
potential for those in the future.
For example, in the future, if we're able to characterize the data we're
collecting on each interrupt, we may be able to inch toward information
theoretic accumulators. <https://eprint.iacr.org/2021/523> shows that `s
= ror32(s, 7) ^ x` and `s = ror64(s, 19) ^ x` make very good
accumulators for 2-monotone distributions, which would apply to
timestamp counters, like random_get_entropy() or jiffies, but would not
apply to our current combination of the two values, or to the various
function addresses and register values we mix in. Alternatively,
<https://eprint.iacr.org/2021/1002> shows that max-period linear
functions with no non-trivial invariant subspace make good extractors,
used in the form `s = f(s) ^ x`. However, this only works if the input
data is both identical and independent, and obviously a collection of
address values and counters fails; so it goes with theoretical papers.
Future directions here may involve trying to characterize more precisely
what we actually need to collect in the interrupt handler, and building
something specific around that.
However, as mentioned, the morass of data we're gathering at the
interrupt handler presently defies characterization, and so we use
SipHash for now, which works well and performs well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-11 14:58:44 +01:00
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random: do not use input pool from hard IRQs
Years ago, a separate fast pool was added for interrupts, so that the
cost associated with taking the input pool spinlocks and mixing into it
would be avoided in places where latency is critical. However, one
oversight was that add_input_randomness() and add_disk_randomness()
still sometimes are called directly from the interrupt handler, rather
than being deferred to a thread. This means that some unlucky interrupts
will be caught doing a blake2s_compress() call and potentially spinning
on input_pool.lock, which can also be taken by unprivileged users by
writing into /dev/urandom.
In order to fix this, add_timer_randomness() now checks whether it is
being called from a hard IRQ and if so, just mixes into the per-cpu IRQ
fast pool using fast_mix(), which is much faster and can be done
lock-free. A nice consequence of this, as well, is that it means hard
IRQ context FPU support is likely no longer useful.
The entropy estimation algorithm used by add_timer_randomness() is also
somewhat different than the one used for add_interrupt_randomness(). The
former looks at deltas of deltas of deltas, while the latter just waits
for 64 interrupts for one bit or for one second since the last bit. In
order to bridge these, and since add_interrupt_randomness() runs after
an add_timer_randomness() that's called from hard IRQ, we add to the
fast pool credit the related amount, and then subtract one to account
for add_interrupt_randomness()'s contribution.
A downside of this, however, is that the num argument is potentially
attacker controlled, which puts a bit more pressure on the fast_mix()
sponge to do more than it's really intended to do. As a mitigating
factor, the first 96 bits of input aren't attacker controlled (a cycle
counter followed by zeros), which means it's essentially two rounds of
siphash rather than one, which is somewhat better. It's also not that
much different from add_interrupt_randomness()'s use of the irq stack
instruction pointer register.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Filipe Manana <fdmanana@suse.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Borislav Petkov <bp@alien8.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-06 18:30:51 +02:00
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random: clear fast pool, crng, and batches in cpuhp bring up
For the irq randomness fast pool, rather than having to use expensive
atomics, which were visibly the most expensive thing in the entire irq
handler, simply take care of the extreme edge case of resetting count to
zero in the cpuhp online handler, just after workqueues have been
reenabled. This simplifies the code a bit and lets us use vanilla
variables rather than atomics, and performance should be improved.
As well, very early on when the CPU comes up, while interrupts are still
disabled, we clear out the per-cpu crng and its batches, so that it
always starts with fresh randomness.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-13 22:48:04 +01:00
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random: defer fast pool mixing to worker
On PREEMPT_RT, it's problematic to take spinlocks from hard irq
handlers. We can fix this by deferring to a workqueue the dumping of
the fast pool into the input pool.
We accomplish this with some careful rules on fast_pool->count:
- When it's incremented to >= 64, we schedule the work.
- If the top bit is set, we never schedule the work, even if >= 64.
- The worker is responsible for setting it back to 0 when it's done.
There are two small issues around using workqueues for this purpose that
we work around.
The first issue is that mix_interrupt_randomness() might be migrated to
another CPU during CPU hotplug. This issue is rectified by checking that
it hasn't been migrated (after disabling irqs). If it has been migrated,
then we set the count to zero, so that when the CPU comes online again,
it can requeue the work. As part of this, we switch to using an
atomic_t, so that the increment in the irq handler doesn't wipe out the
zeroing if the CPU comes back online while this worker is running.
The second issue is that, though relatively minor in effect, we probably
want to make sure we get a consistent view of the pool onto the stack,
in case it's interrupted by an irq while reading. To do this, we don't
reenable irqs until after the copy. There are only 18 instructions
between the cli and sti, so this is a pretty tiny window.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 16:15:46 +01:00
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random: use first 128 bits of input as fast init
Before, the first 64 bytes of input, regardless of how entropic it was,
would be used to mutate the crng base key directly, and none of those
bytes would be credited as having entropy. Then 256 bits of credited
input would be accumulated, and only then would the rng transition from
the earlier "fast init" phase into being actually initialized.
The thinking was that by mixing and matching fast init and real init, an
attacker who compromised the fast init state, considered easy to do
given how little entropy might be in those first 64 bytes, would then be
able to bruteforce bits from the actual initialization. By keeping these
separate, bruteforcing became impossible.
However, by not crediting potentially creditable bits from those first 64
bytes of input, we delay initialization, and actually make the problem
worse, because it means the user is drawing worse random numbers for a
longer period of time.
Instead, we can take the first 128 bits as fast init, and allow them to
be credited, and then hold off on the next 128 bits until they've
accumulated. This is still a wide enough margin to prevent bruteforcing
the rng state, while still initializing much faster.
Then, rather than trying to piecemeal inject into the base crng key at
various points, instead just extract from the pool when we need it, for
the crng_init==0 phase. Performance may even be better for the various
inputs here, since there are likely more calls to mix_pool_bytes() then
there are to get_random_bytes() during this phase of system execution.
Since the preinit injection code is gone, bootloader randomness can then
do something significantly more straight forward, removing the weird
system_wq hack in hwgenerator randomness.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 15:08:20 +02:00
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2022-09-23 02:42:51 +02:00
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random: do crng pre-init loading in worker rather than irq
Taking spinlocks from IRQ context is generally problematic for
PREEMPT_RT. That is, in part, why we take trylocks instead. However, a
spin_try_lock() is also problematic since another spin_lock() invocation
can potentially PI-boost the wrong task, as the spin_try_lock() is
invoked from an IRQ-context, so the task on CPU (random task or idle) is
not the actual owner.
Additionally, by deferring the crng pre-init loading to the worker, we
can use the cryptographic hash function rather than xor, which is
perhaps a meaningful difference when considering this data has only been
through the relatively weak fast_mix() function.
The biggest downside of this approach is that the pre-init loading is
now deferred until later, which means things that need random numbers
after interrupts are enabled, but before workqueues are running -- or
before this particular worker manages to run -- are going to get into
trouble. Hopefully in the real world, this window is rather small,
especially since this code won't run until 64 interrupts had occurred.
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Eric Biggers <ebiggers@kernel.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-13 18:25:07 +01:00
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random: defer fast pool mixing to worker
On PREEMPT_RT, it's problematic to take spinlocks from hard irq
handlers. We can fix this by deferring to a workqueue the dumping of
the fast pool into the input pool.
We accomplish this with some careful rules on fast_pool->count:
- When it's incremented to >= 64, we schedule the work.
- If the top bit is set, we never schedule the work, even if >= 64.
- The worker is responsible for setting it back to 0 when it's done.
There are two small issues around using workqueues for this purpose that
we work around.
The first issue is that mix_interrupt_randomness() might be migrated to
another CPU during CPU hotplug. This issue is rectified by checking that
it hasn't been migrated (after disabling irqs). If it has been migrated,
then we set the count to zero, so that when the CPU comes online again,
it can requeue the work. As part of this, we switch to using an
atomic_t, so that the increment in the irq handler doesn't wipe out the
zeroing if the CPU comes back online while this worker is running.
The second issue is that, though relatively minor in effect, we probably
want to make sure we get a consistent view of the pool onto the stack,
in case it's interrupted by an irq while reading. To do this, we don't
reenable irqs until after the copy. There are only 18 instructions
between the cli and sti, so this is a pretty tiny window.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 16:15:46 +01:00
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2021-12-07 13:17:33 +01:00
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2005-04-16 15:20:36 -07:00
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random: defer fast pool mixing to worker
On PREEMPT_RT, it's problematic to take spinlocks from hard irq
handlers. We can fix this by deferring to a workqueue the dumping of
the fast pool into the input pool.
We accomplish this with some careful rules on fast_pool->count:
- When it's incremented to >= 64, we schedule the work.
- If the top bit is set, we never schedule the work, even if >= 64.
- The worker is responsible for setting it back to 0 when it's done.
There are two small issues around using workqueues for this purpose that
we work around.
The first issue is that mix_interrupt_randomness() might be migrated to
another CPU during CPU hotplug. This issue is rectified by checking that
it hasn't been migrated (after disabling irqs). If it has been migrated,
then we set the count to zero, so that when the CPU comes online again,
it can requeue the work. As part of this, we switch to using an
atomic_t, so that the increment in the irq handler doesn't wipe out the
zeroing if the CPU comes back online while this worker is running.
The second issue is that, though relatively minor in effect, we probably
want to make sure we get a consistent view of the pool onto the stack,
in case it's interrupted by an irq while reading. To do this, we don't
reenable irqs until after the copy. There are only 18 instructions
between the cli and sti, so this is a pretty tiny window.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 16:15:46 +01:00
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random: insist on random_get_entropy() existing in order to simplify
All platforms are now guaranteed to provide some value for
random_get_entropy(). In case some bug leads to this not being so, we
print a warning, because that indicates that something is really very
wrong (and likely other things are impacted too). This should never be
hit, but it's a good and cheap way of finding out if something ever is
problematic.
Since we now have viable fallback code for random_get_entropy() on all
platforms, which is, in the worst case, not worse than jiffies, we can
count on getting the best possible value out of it. That means there's
no longer a use for using jiffies as entropy input. It also means we no
longer have a reason for doing the round-robin register flow in the IRQ
handler, which was always of fairly dubious value.
Instead we can greatly simplify the IRQ handler inputs and also unify
the construction between 64-bits and 32-bits. We now collect the cycle
counter and the return address, since those are the two things that
matter. Because the return address and the irq number are likely
related, to the extent we mix in the irq number, we can just xor it into
the top unchanging bytes of the return address, rather than the bottom
changing bytes of the cycle counter as before. Then, we can do a fixed 2
rounds of SipHash/HSipHash. Finally, we use the same construction of
hashing only half of the [H]SipHash state on 32-bit and 64-bit. We're
not actually discarding any entropy, since that entropy is carried
through until the next time. And more importantly, it lets us do the
same sponge-like construction everywhere.
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-12 19:59:57 +02:00
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2022-01-15 14:57:22 +01:00
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random: defer fast pool mixing to worker
On PREEMPT_RT, it's problematic to take spinlocks from hard irq
handlers. We can fix this by deferring to a workqueue the dumping of
the fast pool into the input pool.
We accomplish this with some careful rules on fast_pool->count:
- When it's incremented to >= 64, we schedule the work.
- If the top bit is set, we never schedule the work, even if >= 64.
- The worker is responsible for setting it back to 0 when it's done.
There are two small issues around using workqueues for this purpose that
we work around.
The first issue is that mix_interrupt_randomness() might be migrated to
another CPU during CPU hotplug. This issue is rectified by checking that
it hasn't been migrated (after disabling irqs). If it has been migrated,
then we set the count to zero, so that when the CPU comes online again,
it can requeue the work. As part of this, we switch to using an
atomic_t, so that the increment in the irq handler doesn't wipe out the
zeroing if the CPU comes back online while this worker is running.
The second issue is that, though relatively minor in effect, we probably
want to make sure we get a consistent view of the pool onto the stack,
in case it's interrupted by an irq while reading. To do this, we don't
reenable irqs until after the copy. There are only 18 instructions
between the cli and sti, so this is a pretty tiny window.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 16:15:46 +01:00
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2022-02-10 17:01:27 +01:00
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2022-05-06 23:19:43 +02:00
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random: clear fast pool, crng, and batches in cpuhp bring up
For the irq randomness fast pool, rather than having to use expensive
atomics, which were visibly the most expensive thing in the entire irq
handler, simply take care of the extreme edge case of resetting count to
zero in the cpuhp online handler, just after workqueues have been
reenabled. This simplifies the code a bit and lets us use vanilla
variables rather than atomics, and performance should be improved.
As well, very early on when the CPU comes up, while interrupts are still
disabled, we clear out the per-cpu crng and its batches, so that it
always starts with fresh randomness.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-13 22:48:04 +01:00
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2008-08-19 20:50:08 -07:00
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random: defer fast pool mixing to worker
On PREEMPT_RT, it's problematic to take spinlocks from hard irq
handlers. We can fix this by deferring to a workqueue the dumping of
the fast pool into the input pool.
We accomplish this with some careful rules on fast_pool->count:
- When it's incremented to >= 64, we schedule the work.
- If the top bit is set, we never schedule the work, even if >= 64.
- The worker is responsible for setting it back to 0 when it's done.
There are two small issues around using workqueues for this purpose that
we work around.
The first issue is that mix_interrupt_randomness() might be migrated to
another CPU during CPU hotplug. This issue is rectified by checking that
it hasn't been migrated (after disabling irqs). If it has been migrated,
then we set the count to zero, so that when the CPU comes online again,
it can requeue the work. As part of this, we switch to using an
atomic_t, so that the increment in the irq handler doesn't wipe out the
zeroing if the CPU comes back online while this worker is running.
The second issue is that, though relatively minor in effect, we probably
want to make sure we get a consistent view of the pool onto the stack,
in case it's interrupted by an irq while reading. To do this, we don't
reenable irqs until after the copy. There are only 18 instructions
between the cli and sti, so this is a pretty tiny window.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Jonathan Neuschäfer <j.neuschaefer@gmx.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Reviewed-by: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-04 16:15:46 +01:00
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2005-04-16 15:20:36 -07:00
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random: schedule mix_interrupt_randomness() less often
It used to be that mix_interrupt_randomness() would credit 1 bit each
time it ran, and so add_interrupt_randomness() would schedule mix() to
run every 64 interrupts, a fairly arbitrary number, but nonetheless
considered to be a decent enough conservative estimate.
Since e3e33fc2ea7f ("random: do not use input pool from hard IRQs"),
mix() is now able to credit multiple bits, depending on the number of
calls to add(). This was done for reasons separate from this commit, but
it has the nice side effect of enabling this patch to schedule mix()
less often.
Currently the rules are:
a) Credit 1 bit for every 64 calls to add().
b) Schedule mix() once a second that add() is called.
c) Schedule mix() once every 64 calls to add().
Rules (a) and (c) no longer need to be coupled. It's still important to
have _some_ value in (c), so that we don't "over-saturate" the fast
pool, but the once per second we get from rule (b) is a plenty enough
baseline. So, by increasing the 64 in rule (c) to something larger, we
avoid calling queue_work_on() as frequently during irq storms.
This commit changes that 64 in rule (c) to be 1024, which means we
schedule mix() 16 times less often. And it does *not* need to change the
64 in rule (a).
Fixes: 58340f8e952b ("random: defer fast pool mixing to worker")
Cc: stable@vger.kernel.org
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-06-16 02:03:12 +02:00
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2014-06-10 22:46:37 -04:00
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2014-03-17 16:36:28 -07:00
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random: clear fast pool, crng, and batches in cpuhp bring up
For the irq randomness fast pool, rather than having to use expensive
atomics, which were visibly the most expensive thing in the entire irq
handler, simply take care of the extreme edge case of resetting count to
zero in the cpuhp online handler, just after workqueues have been
reenabled. This simplifies the code a bit and lets us use vanilla
variables rather than atomics, and performance should be improved.
As well, very early on when the CPU comes up, while interrupts are still
disabled, we clear out the per-cpu crng and its batches, so that it
always starts with fresh randomness.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Acked-by: Sebastian Andrzej Siewior <bigeasy@linutronix.de>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-13 22:48:04 +01:00
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2022-09-22 18:46:04 +02:00
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2005-04-16 15:20:36 -07:00
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2016-05-02 02:14:34 -04:00
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2005-04-16 15:20:36 -07:00
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2022-05-06 18:27:38 +02:00
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random: do not use input pool from hard IRQs
Years ago, a separate fast pool was added for interrupts, so that the
cost associated with taking the input pool spinlocks and mixing into it
would be avoided in places where latency is critical. However, one
oversight was that add_input_randomness() and add_disk_randomness()
still sometimes are called directly from the interrupt handler, rather
than being deferred to a thread. This means that some unlucky interrupts
will be caught doing a blake2s_compress() call and potentially spinning
on input_pool.lock, which can also be taken by unprivileged users by
writing into /dev/urandom.
In order to fix this, add_timer_randomness() now checks whether it is
being called from a hard IRQ and if so, just mixes into the per-cpu IRQ
fast pool using fast_mix(), which is much faster and can be done
lock-free. A nice consequence of this, as well, is that it means hard
IRQ context FPU support is likely no longer useful.
The entropy estimation algorithm used by add_timer_randomness() is also
somewhat different than the one used for add_interrupt_randomness(). The
former looks at deltas of deltas of deltas, while the latter just waits
for 64 interrupts for one bit or for one second since the last bit. In
order to bridge these, and since add_interrupt_randomness() runs after
an add_timer_randomness() that's called from hard IRQ, we add to the
fast pool credit the related amount, and then subtract one to account
for add_interrupt_randomness()'s contribution.
A downside of this, however, is that the num argument is potentially
attacker controlled, which puts a bit more pressure on the fast_mix()
sponge to do more than it's really intended to do. As a mitigating
factor, the first 96 bits of input aren't attacker controlled (a cycle
counter followed by zeros), which means it's essentially two rounds of
siphash rather than one, which is somewhat better. It's also not that
much different from add_interrupt_randomness()'s use of the irq stack
instruction pointer register.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Filipe Manana <fdmanana@suse.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Borislav Petkov <bp@alien8.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-06 18:30:51 +02:00
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2022-05-06 18:27:38 +02:00
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random: do not use input pool from hard IRQs
Years ago, a separate fast pool was added for interrupts, so that the
cost associated with taking the input pool spinlocks and mixing into it
would be avoided in places where latency is critical. However, one
oversight was that add_input_randomness() and add_disk_randomness()
still sometimes are called directly from the interrupt handler, rather
than being deferred to a thread. This means that some unlucky interrupts
will be caught doing a blake2s_compress() call and potentially spinning
on input_pool.lock, which can also be taken by unprivileged users by
writing into /dev/urandom.
In order to fix this, add_timer_randomness() now checks whether it is
being called from a hard IRQ and if so, just mixes into the per-cpu IRQ
fast pool using fast_mix(), which is much faster and can be done
lock-free. A nice consequence of this, as well, is that it means hard
IRQ context FPU support is likely no longer useful.
The entropy estimation algorithm used by add_timer_randomness() is also
somewhat different than the one used for add_interrupt_randomness(). The
former looks at deltas of deltas of deltas, while the latter just waits
for 64 interrupts for one bit or for one second since the last bit. In
order to bridge these, and since add_interrupt_randomness() runs after
an add_timer_randomness() that's called from hard IRQ, we add to the
fast pool credit the related amount, and then subtract one to account
for add_interrupt_randomness()'s contribution.
A downside of this, however, is that the num argument is potentially
attacker controlled, which puts a bit more pressure on the fast_mix()
sponge to do more than it's really intended to do. As a mitigating
factor, the first 96 bits of input aren't attacker controlled (a cycle
counter followed by zeros), which means it's essentially two rounds of
siphash rather than one, which is somewhat better. It's also not that
much different from add_interrupt_randomness()'s use of the irq stack
instruction pointer register.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Filipe Manana <fdmanana@suse.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Borislav Petkov <bp@alien8.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-06 18:30:51 +02:00
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2022-05-06 18:27:38 +02:00
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random: do not use input pool from hard IRQs
Years ago, a separate fast pool was added for interrupts, so that the
cost associated with taking the input pool spinlocks and mixing into it
would be avoided in places where latency is critical. However, one
oversight was that add_input_randomness() and add_disk_randomness()
still sometimes are called directly from the interrupt handler, rather
than being deferred to a thread. This means that some unlucky interrupts
will be caught doing a blake2s_compress() call and potentially spinning
on input_pool.lock, which can also be taken by unprivileged users by
writing into /dev/urandom.
In order to fix this, add_timer_randomness() now checks whether it is
being called from a hard IRQ and if so, just mixes into the per-cpu IRQ
fast pool using fast_mix(), which is much faster and can be done
lock-free. A nice consequence of this, as well, is that it means hard
IRQ context FPU support is likely no longer useful.
The entropy estimation algorithm used by add_timer_randomness() is also
somewhat different than the one used for add_interrupt_randomness(). The
former looks at deltas of deltas of deltas, while the latter just waits
for 64 interrupts for one bit or for one second since the last bit. In
order to bridge these, and since add_interrupt_randomness() runs after
an add_timer_randomness() that's called from hard IRQ, we add to the
fast pool credit the related amount, and then subtract one to account
for add_interrupt_randomness()'s contribution.
A downside of this, however, is that the num argument is potentially
attacker controlled, which puts a bit more pressure on the fast_mix()
sponge to do more than it's really intended to do. As a mitigating
factor, the first 96 bits of input aren't attacker controlled (a cycle
counter followed by zeros), which means it's essentially two rounds of
siphash rather than one, which is somewhat better. It's also not that
much different from add_interrupt_randomness()'s use of the irq stack
instruction pointer register.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Filipe Manana <fdmanana@suse.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Borislav Petkov <bp@alien8.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-06 18:30:51 +02:00
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2022-05-06 23:19:43 +02:00
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random: do not use input pool from hard IRQs
Years ago, a separate fast pool was added for interrupts, so that the
cost associated with taking the input pool spinlocks and mixing into it
would be avoided in places where latency is critical. However, one
oversight was that add_input_randomness() and add_disk_randomness()
still sometimes are called directly from the interrupt handler, rather
than being deferred to a thread. This means that some unlucky interrupts
will be caught doing a blake2s_compress() call and potentially spinning
on input_pool.lock, which can also be taken by unprivileged users by
writing into /dev/urandom.
In order to fix this, add_timer_randomness() now checks whether it is
being called from a hard IRQ and if so, just mixes into the per-cpu IRQ
fast pool using fast_mix(), which is much faster and can be done
lock-free. A nice consequence of this, as well, is that it means hard
IRQ context FPU support is likely no longer useful.
The entropy estimation algorithm used by add_timer_randomness() is also
somewhat different than the one used for add_interrupt_randomness(). The
former looks at deltas of deltas of deltas, while the latter just waits
for 64 interrupts for one bit or for one second since the last bit. In
order to bridge these, and since add_interrupt_randomness() runs after
an add_timer_randomness() that's called from hard IRQ, we add to the
fast pool credit the related amount, and then subtract one to account
for add_interrupt_randomness()'s contribution.
A downside of this, however, is that the num argument is potentially
attacker controlled, which puts a bit more pressure on the fast_mix()
sponge to do more than it's really intended to do. As a mitigating
factor, the first 96 bits of input aren't attacker controlled (a cycle
counter followed by zeros), which means it's essentially two rounds of
siphash rather than one, which is somewhat better. It's also not that
much different from add_interrupt_randomness()'s use of the irq stack
instruction pointer register.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Filipe Manana <fdmanana@suse.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Borislav Petkov <bp@alien8.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-06 18:30:51 +02:00
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2022-05-06 18:27:38 +02:00
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random: do not use input pool from hard IRQs
Years ago, a separate fast pool was added for interrupts, so that the
cost associated with taking the input pool spinlocks and mixing into it
would be avoided in places where latency is critical. However, one
oversight was that add_input_randomness() and add_disk_randomness()
still sometimes are called directly from the interrupt handler, rather
than being deferred to a thread. This means that some unlucky interrupts
will be caught doing a blake2s_compress() call and potentially spinning
on input_pool.lock, which can also be taken by unprivileged users by
writing into /dev/urandom.
In order to fix this, add_timer_randomness() now checks whether it is
being called from a hard IRQ and if so, just mixes into the per-cpu IRQ
fast pool using fast_mix(), which is much faster and can be done
lock-free. A nice consequence of this, as well, is that it means hard
IRQ context FPU support is likely no longer useful.
The entropy estimation algorithm used by add_timer_randomness() is also
somewhat different than the one used for add_interrupt_randomness(). The
former looks at deltas of deltas of deltas, while the latter just waits
for 64 interrupts for one bit or for one second since the last bit. In
order to bridge these, and since add_interrupt_randomness() runs after
an add_timer_randomness() that's called from hard IRQ, we add to the
fast pool credit the related amount, and then subtract one to account
for add_interrupt_randomness()'s contribution.
A downside of this, however, is that the num argument is potentially
attacker controlled, which puts a bit more pressure on the fast_mix()
sponge to do more than it's really intended to do. As a mitigating
factor, the first 96 bits of input aren't attacker controlled (a cycle
counter followed by zeros), which means it's essentially two rounds of
siphash rather than one, which is somewhat better. It's also not that
much different from add_interrupt_randomness()'s use of the irq stack
instruction pointer register.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Filipe Manana <fdmanana@suse.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Borislav Petkov <bp@alien8.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-06 18:30:51 +02:00
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2022-05-06 18:27:38 +02:00
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random: do not use input pool from hard IRQs
Years ago, a separate fast pool was added for interrupts, so that the
cost associated with taking the input pool spinlocks and mixing into it
would be avoided in places where latency is critical. However, one
oversight was that add_input_randomness() and add_disk_randomness()
still sometimes are called directly from the interrupt handler, rather
than being deferred to a thread. This means that some unlucky interrupts
will be caught doing a blake2s_compress() call and potentially spinning
on input_pool.lock, which can also be taken by unprivileged users by
writing into /dev/urandom.
In order to fix this, add_timer_randomness() now checks whether it is
being called from a hard IRQ and if so, just mixes into the per-cpu IRQ
fast pool using fast_mix(), which is much faster and can be done
lock-free. A nice consequence of this, as well, is that it means hard
IRQ context FPU support is likely no longer useful.
The entropy estimation algorithm used by add_timer_randomness() is also
somewhat different than the one used for add_interrupt_randomness(). The
former looks at deltas of deltas of deltas, while the latter just waits
for 64 interrupts for one bit or for one second since the last bit. In
order to bridge these, and since add_interrupt_randomness() runs after
an add_timer_randomness() that's called from hard IRQ, we add to the
fast pool credit the related amount, and then subtract one to account
for add_interrupt_randomness()'s contribution.
A downside of this, however, is that the num argument is potentially
attacker controlled, which puts a bit more pressure on the fast_mix()
sponge to do more than it's really intended to do. As a mitigating
factor, the first 96 bits of input aren't attacker controlled (a cycle
counter followed by zeros), which means it's essentially two rounds of
siphash rather than one, which is somewhat better. It's also not that
much different from add_interrupt_randomness()'s use of the irq stack
instruction pointer register.
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Filipe Manana <fdmanana@suse.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Borislav Petkov <bp@alien8.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-06 18:30:51 +02:00
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2022-05-13 16:17:12 +02:00
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2022-05-06 18:27:38 +02:00
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2022-05-13 13:18:46 +02:00
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2022-05-06 18:27:38 +02:00
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2022-05-13 16:17:12 +02:00
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2022-05-06 18:27:38 +02:00
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random: vary jitter iterations based on cycle counter speed
Currently, we do the jitter dance if two consecutive reads to the cycle
counter return different values. If they do, then we consider the cycle
counter to be fast enough that one trip through the scheduler will yield
one "bit" of credited entropy. If those two reads return the same value,
then we assume the cycle counter is too slow to show meaningful
differences.
This methodology is flawed for a variety of reasons, one of which Eric
posted a patch to fix in [1]. The issue that patch solves is that on a
system with a slow counter, you might be [un]lucky and read the counter
_just_ before it changes, so that the second cycle counter you read
differs from the first, even though there's usually quite a large period
of time in between the two. For example:
| real time | cycle counter |
| --------- | ------------- |
| 3 | 5 |
| 4 | 5 |
| 5 | 5 |
| 6 | 5 |
| 7 | 5 | <--- a
| 8 | 6 | <--- b
| 9 | 6 | <--- c
If we read the counter at (a) and compare it to (b), we might be fooled
into thinking that it's a fast counter, when in reality it is not. The
solution in [1] is to also compare counter (b) to counter (c), on the
theory that if the counter is _actually_ slow, and (a)!=(b), then
certainly (b)==(c).
This helps solve this particular issue, in one sense, but in another
sense, it mostly functions to disallow jitter entropy on these systems,
rather than simply taking more samples in that case.
Instead, this patch takes a different approach. Right now we assume that
a difference in one set of consecutive samples means one "bit" of
credited entropy per scheduler trip. We can extend this so that a
difference in two sets of consecutive samples means one "bit" of
credited entropy per /two/ scheduler trips, and three for three, and
four for four. In other words, we can increase the amount of jitter
"work" we require for each "bit", depending on how slow the cycle
counter is.
So this patch takes whole bunch of samples, sees how many of them are
different, and divides to find the amount of work required per "bit",
and also requires that at least some minimum of them are different in
order to attempt any jitter entropy.
Note that this approach is still far from perfect. It's not a real
statistical estimate on how much these samples vary; it's not a
real-time analysis of the relevant input data. That remains a project
for another time. However, it makes the same (partly flawed) assumptions
as the code that's there now, so it's probably not worse than the status
quo, and it handles the issue Eric mentioned in [1]. But, again, it's
probably a far cry from whatever a really robust version of this would
be.
[1] https://lore.kernel.org/lkml/20220421233152.58522-1-ebiggers@kernel.org/
https://lore.kernel.org/lkml/20220421192939.250680-1-ebiggers@kernel.org/
Cc: Eric Biggers <ebiggers@google.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-22 14:47:42 +02:00
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2022-10-01 01:10:50 +02:00
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random: vary jitter iterations based on cycle counter speed
Currently, we do the jitter dance if two consecutive reads to the cycle
counter return different values. If they do, then we consider the cycle
counter to be fast enough that one trip through the scheduler will yield
one "bit" of credited entropy. If those two reads return the same value,
then we assume the cycle counter is too slow to show meaningful
differences.
This methodology is flawed for a variety of reasons, one of which Eric
posted a patch to fix in [1]. The issue that patch solves is that on a
system with a slow counter, you might be [un]lucky and read the counter
_just_ before it changes, so that the second cycle counter you read
differs from the first, even though there's usually quite a large period
of time in between the two. For example:
| real time | cycle counter |
| --------- | ------------- |
| 3 | 5 |
| 4 | 5 |
| 5 | 5 |
| 6 | 5 |
| 7 | 5 | <--- a
| 8 | 6 | <--- b
| 9 | 6 | <--- c
If we read the counter at (a) and compare it to (b), we might be fooled
into thinking that it's a fast counter, when in reality it is not. The
solution in [1] is to also compare counter (b) to counter (c), on the
theory that if the counter is _actually_ slow, and (a)!=(b), then
certainly (b)==(c).
This helps solve this particular issue, in one sense, but in another
sense, it mostly functions to disallow jitter entropy on these systems,
rather than simply taking more samples in that case.
Instead, this patch takes a different approach. Right now we assume that
a difference in one set of consecutive samples means one "bit" of
credited entropy per scheduler trip. We can extend this so that a
difference in two sets of consecutive samples means one "bit" of
credited entropy per /two/ scheduler trips, and three for three, and
four for four. In other words, we can increase the amount of jitter
"work" we require for each "bit", depending on how slow the cycle
counter is.
So this patch takes whole bunch of samples, sees how many of them are
different, and divides to find the amount of work required per "bit",
and also requires that at least some minimum of them are different in
order to attempt any jitter entropy.
Note that this approach is still far from perfect. It's not a real
statistical estimate on how much these samples vary; it's not a
real-time analysis of the relevant input data. That remains a project
for another time. However, it makes the same (partly flawed) assumptions
as the code that's there now, so it's probably not worse than the status
quo, and it handles the issue Eric mentioned in [1]. But, again, it's
probably a far cry from whatever a really robust version of this would
be.
[1] https://lore.kernel.org/lkml/20220421233152.58522-1-ebiggers@kernel.org/
https://lore.kernel.org/lkml/20220421192939.250680-1-ebiggers@kernel.org/
Cc: Eric Biggers <ebiggers@google.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-22 14:47:42 +02:00
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random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
|
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|
2022-11-29 01:55:11 +01:00
|
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|
random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
|
|
|
|
2022-11-29 01:55:11 +01:00
|
|
|
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|
random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
|
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|
2022-05-13 16:17:12 +02:00
|
|
|
|
random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
|
|
|
|
random: vary jitter iterations based on cycle counter speed
Currently, we do the jitter dance if two consecutive reads to the cycle
counter return different values. If they do, then we consider the cycle
counter to be fast enough that one trip through the scheduler will yield
one "bit" of credited entropy. If those two reads return the same value,
then we assume the cycle counter is too slow to show meaningful
differences.
This methodology is flawed for a variety of reasons, one of which Eric
posted a patch to fix in [1]. The issue that patch solves is that on a
system with a slow counter, you might be [un]lucky and read the counter
_just_ before it changes, so that the second cycle counter you read
differs from the first, even though there's usually quite a large period
of time in between the two. For example:
| real time | cycle counter |
| --------- | ------------- |
| 3 | 5 |
| 4 | 5 |
| 5 | 5 |
| 6 | 5 |
| 7 | 5 | <--- a
| 8 | 6 | <--- b
| 9 | 6 | <--- c
If we read the counter at (a) and compare it to (b), we might be fooled
into thinking that it's a fast counter, when in reality it is not. The
solution in [1] is to also compare counter (b) to counter (c), on the
theory that if the counter is _actually_ slow, and (a)!=(b), then
certainly (b)==(c).
This helps solve this particular issue, in one sense, but in another
sense, it mostly functions to disallow jitter entropy on these systems,
rather than simply taking more samples in that case.
Instead, this patch takes a different approach. Right now we assume that
a difference in one set of consecutive samples means one "bit" of
credited entropy per scheduler trip. We can extend this so that a
difference in two sets of consecutive samples means one "bit" of
credited entropy per /two/ scheduler trips, and three for three, and
four for four. In other words, we can increase the amount of jitter
"work" we require for each "bit", depending on how slow the cycle
counter is.
So this patch takes whole bunch of samples, sees how many of them are
different, and divides to find the amount of work required per "bit",
and also requires that at least some minimum of them are different in
order to attempt any jitter entropy.
Note that this approach is still far from perfect. It's not a real
statistical estimate on how much these samples vary; it's not a
real-time analysis of the relevant input data. That remains a project
for another time. However, it makes the same (partly flawed) assumptions
as the code that's there now, so it's probably not worse than the status
quo, and it handles the issue Eric mentioned in [1]. But, again, it's
probably a far cry from whatever a really robust version of this would
be.
[1] https://lore.kernel.org/lkml/20220421233152.58522-1-ebiggers@kernel.org/
https://lore.kernel.org/lkml/20220421192939.250680-1-ebiggers@kernel.org/
Cc: Eric Biggers <ebiggers@google.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-22 14:47:42 +02:00
|
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|
|
2022-11-30 03:14:15 +01:00
|
|
|
|
random: vary jitter iterations based on cycle counter speed
Currently, we do the jitter dance if two consecutive reads to the cycle
counter return different values. If they do, then we consider the cycle
counter to be fast enough that one trip through the scheduler will yield
one "bit" of credited entropy. If those two reads return the same value,
then we assume the cycle counter is too slow to show meaningful
differences.
This methodology is flawed for a variety of reasons, one of which Eric
posted a patch to fix in [1]. The issue that patch solves is that on a
system with a slow counter, you might be [un]lucky and read the counter
_just_ before it changes, so that the second cycle counter you read
differs from the first, even though there's usually quite a large period
of time in between the two. For example:
| real time | cycle counter |
| --------- | ------------- |
| 3 | 5 |
| 4 | 5 |
| 5 | 5 |
| 6 | 5 |
| 7 | 5 | <--- a
| 8 | 6 | <--- b
| 9 | 6 | <--- c
If we read the counter at (a) and compare it to (b), we might be fooled
into thinking that it's a fast counter, when in reality it is not. The
solution in [1] is to also compare counter (b) to counter (c), on the
theory that if the counter is _actually_ slow, and (a)!=(b), then
certainly (b)==(c).
This helps solve this particular issue, in one sense, but in another
sense, it mostly functions to disallow jitter entropy on these systems,
rather than simply taking more samples in that case.
Instead, this patch takes a different approach. Right now we assume that
a difference in one set of consecutive samples means one "bit" of
credited entropy per scheduler trip. We can extend this so that a
difference in two sets of consecutive samples means one "bit" of
credited entropy per /two/ scheduler trips, and three for three, and
four for four. In other words, we can increase the amount of jitter
"work" we require for each "bit", depending on how slow the cycle
counter is.
So this patch takes whole bunch of samples, sees how many of them are
different, and divides to find the amount of work required per "bit",
and also requires that at least some minimum of them are different in
order to attempt any jitter entropy.
Note that this approach is still far from perfect. It's not a real
statistical estimate on how much these samples vary; it's not a
real-time analysis of the relevant input data. That remains a project
for another time. However, it makes the same (partly flawed) assumptions
as the code that's there now, so it's probably not worse than the status
quo, and it handles the issue Eric mentioned in [1]. But, again, it's
probably a far cry from whatever a really robust version of this would
be.
[1] https://lore.kernel.org/lkml/20220421233152.58522-1-ebiggers@kernel.org/
https://lore.kernel.org/lkml/20220421192939.250680-1-ebiggers@kernel.org/
Cc: Eric Biggers <ebiggers@google.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-22 14:47:42 +02:00
|
|
|
|
2022-11-30 03:14:15 +01:00
|
|
|
|
2022-10-01 01:10:50 +02:00
|
|
|
|
random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
|
|
|
|
random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2022-11-29 01:55:11 +01:00
|
|
|
|
|
|
|
|
|
random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
|
|
|
|
2022-05-13 16:17:12 +02:00
|
|
|
|
random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
|
|
|
|
2022-10-01 00:31:00 +02:00
|
|
|
|
2022-11-30 03:02:05 +01:00
|
|
|
|
|
|
|
|
|
random: vary jitter iterations based on cycle counter speed
Currently, we do the jitter dance if two consecutive reads to the cycle
counter return different values. If they do, then we consider the cycle
counter to be fast enough that one trip through the scheduler will yield
one "bit" of credited entropy. If those two reads return the same value,
then we assume the cycle counter is too slow to show meaningful
differences.
This methodology is flawed for a variety of reasons, one of which Eric
posted a patch to fix in [1]. The issue that patch solves is that on a
system with a slow counter, you might be [un]lucky and read the counter
_just_ before it changes, so that the second cycle counter you read
differs from the first, even though there's usually quite a large period
of time in between the two. For example:
| real time | cycle counter |
| --------- | ------------- |
| 3 | 5 |
| 4 | 5 |
| 5 | 5 |
| 6 | 5 |
| 7 | 5 | <--- a
| 8 | 6 | <--- b
| 9 | 6 | <--- c
If we read the counter at (a) and compare it to (b), we might be fooled
into thinking that it's a fast counter, when in reality it is not. The
solution in [1] is to also compare counter (b) to counter (c), on the
theory that if the counter is _actually_ slow, and (a)!=(b), then
certainly (b)==(c).
This helps solve this particular issue, in one sense, but in another
sense, it mostly functions to disallow jitter entropy on these systems,
rather than simply taking more samples in that case.
Instead, this patch takes a different approach. Right now we assume that
a difference in one set of consecutive samples means one "bit" of
credited entropy per scheduler trip. We can extend this so that a
difference in two sets of consecutive samples means one "bit" of
credited entropy per /two/ scheduler trips, and three for three, and
four for four. In other words, we can increase the amount of jitter
"work" we require for each "bit", depending on how slow the cycle
counter is.
So this patch takes whole bunch of samples, sees how many of them are
different, and divides to find the amount of work required per "bit",
and also requires that at least some minimum of them are different in
order to attempt any jitter entropy.
Note that this approach is still far from perfect. It's not a real
statistical estimate on how much these samples vary; it's not a
real-time analysis of the relevant input data. That remains a project
for another time. However, it makes the same (partly flawed) assumptions
as the code that's there now, so it's probably not worse than the status
quo, and it handles the issue Eric mentioned in [1]. But, again, it's
probably a far cry from whatever a really robust version of this would
be.
[1] https://lore.kernel.org/lkml/20220421233152.58522-1-ebiggers@kernel.org/
https://lore.kernel.org/lkml/20220421192939.250680-1-ebiggers@kernel.org/
Cc: Eric Biggers <ebiggers@google.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-22 14:47:42 +02:00
|
|
|
|
|
|
|
|
|
2022-10-01 01:10:50 +02:00
|
|
|
|
random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
|
|
|
|
random: vary jitter iterations based on cycle counter speed
Currently, we do the jitter dance if two consecutive reads to the cycle
counter return different values. If they do, then we consider the cycle
counter to be fast enough that one trip through the scheduler will yield
one "bit" of credited entropy. If those two reads return the same value,
then we assume the cycle counter is too slow to show meaningful
differences.
This methodology is flawed for a variety of reasons, one of which Eric
posted a patch to fix in [1]. The issue that patch solves is that on a
system with a slow counter, you might be [un]lucky and read the counter
_just_ before it changes, so that the second cycle counter you read
differs from the first, even though there's usually quite a large period
of time in between the two. For example:
| real time | cycle counter |
| --------- | ------------- |
| 3 | 5 |
| 4 | 5 |
| 5 | 5 |
| 6 | 5 |
| 7 | 5 | <--- a
| 8 | 6 | <--- b
| 9 | 6 | <--- c
If we read the counter at (a) and compare it to (b), we might be fooled
into thinking that it's a fast counter, when in reality it is not. The
solution in [1] is to also compare counter (b) to counter (c), on the
theory that if the counter is _actually_ slow, and (a)!=(b), then
certainly (b)==(c).
This helps solve this particular issue, in one sense, but in another
sense, it mostly functions to disallow jitter entropy on these systems,
rather than simply taking more samples in that case.
Instead, this patch takes a different approach. Right now we assume that
a difference in one set of consecutive samples means one "bit" of
credited entropy per scheduler trip. We can extend this so that a
difference in two sets of consecutive samples means one "bit" of
credited entropy per /two/ scheduler trips, and three for three, and
four for four. In other words, we can increase the amount of jitter
"work" we require for each "bit", depending on how slow the cycle
counter is.
So this patch takes whole bunch of samples, sees how many of them are
different, and divides to find the amount of work required per "bit",
and also requires that at least some minimum of them are different in
order to attempt any jitter entropy.
Note that this approach is still far from perfect. It's not a real
statistical estimate on how much these samples vary; it's not a
real-time analysis of the relevant input data. That remains a project
for another time. However, it makes the same (partly flawed) assumptions
as the code that's there now, so it's probably not worse than the status
quo, and it handles the issue Eric mentioned in [1]. But, again, it's
probably a far cry from whatever a really robust version of this would
be.
[1] https://lore.kernel.org/lkml/20220421233152.58522-1-ebiggers@kernel.org/
https://lore.kernel.org/lkml/20220421192939.250680-1-ebiggers@kernel.org/
Cc: Eric Biggers <ebiggers@google.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-22 14:47:42 +02:00
|
|
|
|
2022-11-30 03:02:05 +01:00
|
|
|
|
|
|
|
|
|
random: vary jitter iterations based on cycle counter speed
Currently, we do the jitter dance if two consecutive reads to the cycle
counter return different values. If they do, then we consider the cycle
counter to be fast enough that one trip through the scheduler will yield
one "bit" of credited entropy. If those two reads return the same value,
then we assume the cycle counter is too slow to show meaningful
differences.
This methodology is flawed for a variety of reasons, one of which Eric
posted a patch to fix in [1]. The issue that patch solves is that on a
system with a slow counter, you might be [un]lucky and read the counter
_just_ before it changes, so that the second cycle counter you read
differs from the first, even though there's usually quite a large period
of time in between the two. For example:
| real time | cycle counter |
| --------- | ------------- |
| 3 | 5 |
| 4 | 5 |
| 5 | 5 |
| 6 | 5 |
| 7 | 5 | <--- a
| 8 | 6 | <--- b
| 9 | 6 | <--- c
If we read the counter at (a) and compare it to (b), we might be fooled
into thinking that it's a fast counter, when in reality it is not. The
solution in [1] is to also compare counter (b) to counter (c), on the
theory that if the counter is _actually_ slow, and (a)!=(b), then
certainly (b)==(c).
This helps solve this particular issue, in one sense, but in another
sense, it mostly functions to disallow jitter entropy on these systems,
rather than simply taking more samples in that case.
Instead, this patch takes a different approach. Right now we assume that
a difference in one set of consecutive samples means one "bit" of
credited entropy per scheduler trip. We can extend this so that a
difference in two sets of consecutive samples means one "bit" of
credited entropy per /two/ scheduler trips, and three for three, and
four for four. In other words, we can increase the amount of jitter
"work" we require for each "bit", depending on how slow the cycle
counter is.
So this patch takes whole bunch of samples, sees how many of them are
different, and divides to find the amount of work required per "bit",
and also requires that at least some minimum of them are different in
order to attempt any jitter entropy.
Note that this approach is still far from perfect. It's not a real
statistical estimate on how much these samples vary; it's not a
real-time analysis of the relevant input data. That remains a project
for another time. However, it makes the same (partly flawed) assumptions
as the code that's there now, so it's probably not worse than the status
quo, and it handles the issue Eric mentioned in [1]. But, again, it's
probably a far cry from whatever a really robust version of this would
be.
[1] https://lore.kernel.org/lkml/20220421233152.58522-1-ebiggers@kernel.org/
https://lore.kernel.org/lkml/20220421192939.250680-1-ebiggers@kernel.org/
Cc: Eric Biggers <ebiggers@google.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-22 14:47:42 +02:00
|
|
|
|
2022-11-30 03:02:05 +01:00
|
|
|
|
random: vary jitter iterations based on cycle counter speed
Currently, we do the jitter dance if two consecutive reads to the cycle
counter return different values. If they do, then we consider the cycle
counter to be fast enough that one trip through the scheduler will yield
one "bit" of credited entropy. If those two reads return the same value,
then we assume the cycle counter is too slow to show meaningful
differences.
This methodology is flawed for a variety of reasons, one of which Eric
posted a patch to fix in [1]. The issue that patch solves is that on a
system with a slow counter, you might be [un]lucky and read the counter
_just_ before it changes, so that the second cycle counter you read
differs from the first, even though there's usually quite a large period
of time in between the two. For example:
| real time | cycle counter |
| --------- | ------------- |
| 3 | 5 |
| 4 | 5 |
| 5 | 5 |
| 6 | 5 |
| 7 | 5 | <--- a
| 8 | 6 | <--- b
| 9 | 6 | <--- c
If we read the counter at (a) and compare it to (b), we might be fooled
into thinking that it's a fast counter, when in reality it is not. The
solution in [1] is to also compare counter (b) to counter (c), on the
theory that if the counter is _actually_ slow, and (a)!=(b), then
certainly (b)==(c).
This helps solve this particular issue, in one sense, but in another
sense, it mostly functions to disallow jitter entropy on these systems,
rather than simply taking more samples in that case.
Instead, this patch takes a different approach. Right now we assume that
a difference in one set of consecutive samples means one "bit" of
credited entropy per scheduler trip. We can extend this so that a
difference in two sets of consecutive samples means one "bit" of
credited entropy per /two/ scheduler trips, and three for three, and
four for four. In other words, we can increase the amount of jitter
"work" we require for each "bit", depending on how slow the cycle
counter is.
So this patch takes whole bunch of samples, sees how many of them are
different, and divides to find the amount of work required per "bit",
and also requires that at least some minimum of them are different in
order to attempt any jitter entropy.
Note that this approach is still far from perfect. It's not a real
statistical estimate on how much these samples vary; it's not a
real-time analysis of the relevant input data. That remains a project
for another time. However, it makes the same (partly flawed) assumptions
as the code that's there now, so it's probably not worse than the status
quo, and it handles the issue Eric mentioned in [1]. But, again, it's
probably a far cry from whatever a really robust version of this would
be.
[1] https://lore.kernel.org/lkml/20220421233152.58522-1-ebiggers@kernel.org/
https://lore.kernel.org/lkml/20220421192939.250680-1-ebiggers@kernel.org/
Cc: Eric Biggers <ebiggers@google.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-22 14:47:42 +02:00
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2022-11-30 03:02:05 +01:00
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random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
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2022-11-30 03:02:05 +01:00
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random: check for signal and try earlier when generating entropy
Rather than waiting a full second in an interruptable waiter before
trying to generate entropy, try to generate entropy first and wait
second. While waiting one second might give an extra second for getting
entropy from elsewhere, we're already pretty late in the init process
here, and whatever else is generating entropy will still continue to
contribute. This has implications on signal handling: we call
try_to_generate_entropy() from wait_for_random_bytes(), and
wait_for_random_bytes() always uses wait_event_interruptible_timeout()
when waiting, since it's called by userspace code in restartable
contexts, where signals can pend. Since try_to_generate_entropy() now
runs first, if a signal is pending, it's necessary for
try_to_generate_entropy() to check for signals, since it won't hit the
wait until after try_to_generate_entropy() has returned. And even before
this change, when entering a busy loop in try_to_generate_entropy(), we
should have been checking to see if any signals are pending, so that a
process doesn't get stuck in that loop longer than expected.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-08 10:12:16 -07:00
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2022-10-01 01:10:50 +02:00
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2022-11-30 03:02:05 +01:00
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2022-10-01 01:10:50 +02:00
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2023-03-06 12:15:13 -08:00
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2022-10-01 01:10:50 +02:00
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2022-11-30 03:02:05 +01:00
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2022-10-01 01:10:50 +02:00
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2022-11-30 03:02:05 +01:00
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2022-10-01 01:10:50 +02:00
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2022-11-30 03:02:05 +01:00
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random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
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2022-11-30 03:02:05 +01:00
|
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|
random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
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2022-11-30 03:02:05 +01:00
|
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random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
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2022-11-30 03:02:05 +01:00
|
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random: try to actively add entropy rather than passively wait for it
For 5.3 we had to revert a nice ext4 IO pattern improvement, because it
caused a bootup regression due to lack of entropy at bootup together
with arguably broken user space that was asking for secure random
numbers when it really didn't need to.
See commit 72dbcf721566 (Revert "ext4: make __ext4_get_inode_loc plug").
This aims to solve the issue by actively generating entropy noise using
the CPU cycle counter when waiting for the random number generator to
initialize. This only works when you have a high-frequency time stamp
counter available, but that's the case on all modern x86 CPU's, and on
most other modern CPU's too.
What we do is to generate jitter entropy from the CPU cycle counter
under a somewhat complex load: calling the scheduler while also
guaranteeing a certain amount of timing noise by also triggering a
timer.
I'm sure we can tweak this, and that people will want to look at other
alternatives, but there's been a number of papers written on jitter
entropy, and this should really be fairly conservative by crediting one
bit of entropy for every timer-induced jump in the cycle counter. Not
because the timer itself would be all that unpredictable, but because
the interaction between the timer and the loop is going to be.
Even if (and perhaps particularly if) the timer actually happens on
another CPU, the cacheline interaction between the loop that reads the
cycle counter and the timer itself firing is going to add perturbations
to the cycle counter values that get mixed into the entropy pool.
As Thomas pointed out, with a modern out-of-order CPU, even quite simple
loops show a fair amount of hard-to-predict timing variability even in
the absense of external interrupts. But this tries to take that further
by actually having a fairly complex interaction.
This is not going to solve the entropy issue for architectures that have
no CPU cycle counter, but it's not clear how (and if) that is solvable,
and the hardware in question is largely starting to be irrelevant. And
by doing this we can at least avoid some of the even more contentious
approaches (like making the entropy waiting time out in order to avoid
the possibly unbounded waiting).
Cc: Ahmed Darwish <darwish.07@gmail.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nicholas Mc Guire <hofrat@opentech.at>
Cc: Andy Lutomirski <luto@kernel.org>
Cc: Kees Cook <keescook@chromium.org>
Cc: Willy Tarreau <w@1wt.eu>
Cc: Alexander E. Patrakov <patrakov@gmail.com>
Cc: Lennart Poettering <mzxreary@0pointer.de>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-09-28 16:53:52 -07:00
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2022-02-11 12:53:34 +01:00
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2022-03-22 09:17:20 -07:00
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2022-02-11 12:53:34 +01:00
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2022-03-22 09:17:20 -07:00
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2022-02-11 12:53:34 +01:00
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2022-05-13 13:18:46 +02:00
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2005-04-16 15:20:36 -07:00
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2022-05-19 17:31:36 -06:00
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2022-02-11 12:53:34 +01:00
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2013-11-03 06:54:51 -05:00
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2022-02-11 12:53:34 +01:00
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2019-12-23 00:20:45 -08:00
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random: use static branch for crng_ready()
Since crng_ready() is only false briefly during initialization and then
forever after becomes true, we don't need to evaluate it after, making
it a prime candidate for a static branch.
One complication, however, is that it changes state in a particular call
to credit_init_bits(), which might be made from atomic context, which
means we must kick off a workqueue to change the static key. Further
complicating things, credit_init_bits() may be called sufficiently early
on in system initialization such that system_wq is NULL.
Fortunately, there exists the nice function execute_in_process_context(),
which will immediately execute the function if !in_interrupt(), and
otherwise defer it to a workqueue. During early init, before workqueues
are available, in_interrupt() is always false, because interrupts
haven't even been enabled yet, which means the function in that case
executes immediately. Later on, after workqueues are available,
in_interrupt() might be true, but in that case, the work is queued in
system_wq and all goes well.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Sultan Alsawaf <sultan@kerneltoast.com>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-03 15:30:45 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-19 17:31:36 -06:00
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2022-09-15 20:25:47 -04:00
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2022-05-19 17:31:36 -06:00
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2019-12-23 00:20:48 -08:00
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2022-01-15 14:57:22 +01:00
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2005-04-16 15:20:36 -07:00
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2019-12-23 00:20:48 -08:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2005-04-16 15:20:36 -07:00
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random: check for signals after page of pool writes
get_random_bytes_user() checks for signals after producing a PAGE_SIZE
worth of output, just like /dev/zero does. write_pool() is doing
basically the same work (actually, slightly more expensive), and so
should stop to check for signals in the same way. Let's also name it
write_pool_user() to match get_random_bytes_user(), so this won't be
misused in the future.
Before this patch, massive writes to /dev/urandom would tie up the
process for an extremely long time and make it unterminatable. After, it
can be successfully interrupted. The following test program can be used
to see this works as intended:
#include <unistd.h>
#include <fcntl.h>
#include <signal.h>
#include <stdio.h>
static unsigned char x[~0U];
static void handle(int) { }
int main(int argc, char *argv[])
{
pid_t pid = getpid(), child;
int fd;
signal(SIGUSR1, handle);
if (!(child = fork())) {
for (;;)
kill(pid, SIGUSR1);
}
fd = open("/dev/urandom", O_WRONLY);
pause();
printf("interrupted after writing %zd bytes\n", write(fd, x, sizeof(x)));
close(fd);
kill(child, SIGTERM);
return 0;
}
Result before: "interrupted after writing 2147479552 bytes"
Result after: "interrupted after writing 4096 bytes"
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-22 22:25:41 +02:00
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2005-04-16 15:20:36 -07:00
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2022-02-09 14:43:25 +01:00
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2022-05-19 17:43:15 -06:00
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2005-04-16 15:20:36 -07:00
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2022-05-19 17:43:15 -06:00
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random: check for signals after page of pool writes
get_random_bytes_user() checks for signals after producing a PAGE_SIZE
worth of output, just like /dev/zero does. write_pool() is doing
basically the same work (actually, slightly more expensive), and so
should stop to check for signals in the same way. Let's also name it
write_pool_user() to match get_random_bytes_user(), so this won't be
misused in the future.
Before this patch, massive writes to /dev/urandom would tie up the
process for an extremely long time and make it unterminatable. After, it
can be successfully interrupted. The following test program can be used
to see this works as intended:
#include <unistd.h>
#include <fcntl.h>
#include <signal.h>
#include <stdio.h>
static unsigned char x[~0U];
static void handle(int) { }
int main(int argc, char *argv[])
{
pid_t pid = getpid(), child;
int fd;
signal(SIGUSR1, handle);
if (!(child = fork())) {
for (;;)
kill(pid, SIGUSR1);
}
fd = open("/dev/urandom", O_WRONLY);
pause();
printf("interrupted after writing %zd bytes\n", write(fd, x, sizeof(x)));
close(fd);
kill(child, SIGTERM);
return 0;
}
Result before: "interrupted after writing 2147479552 bytes"
Result after: "interrupted after writing 4096 bytes"
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-22 22:25:41 +02:00
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2005-04-16 15:20:36 -07:00
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2007-05-29 21:58:10 -05:00
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2022-02-09 18:42:13 +01:00
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2022-05-19 17:43:15 -06:00
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2007-05-29 21:58:10 -05:00
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2022-05-19 17:43:15 -06:00
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2007-05-29 21:58:10 -05:00
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random: check for signals after page of pool writes
get_random_bytes_user() checks for signals after producing a PAGE_SIZE
worth of output, just like /dev/zero does. write_pool() is doing
basically the same work (actually, slightly more expensive), and so
should stop to check for signals in the same way. Let's also name it
write_pool_user() to match get_random_bytes_user(), so this won't be
misused in the future.
Before this patch, massive writes to /dev/urandom would tie up the
process for an extremely long time and make it unterminatable. After, it
can be successfully interrupted. The following test program can be used
to see this works as intended:
#include <unistd.h>
#include <fcntl.h>
#include <signal.h>
#include <stdio.h>
static unsigned char x[~0U];
static void handle(int) { }
int main(int argc, char *argv[])
{
pid_t pid = getpid(), child;
int fd;
signal(SIGUSR1, handle);
if (!(child = fork())) {
for (;;)
kill(pid, SIGUSR1);
}
fd = open("/dev/urandom", O_WRONLY);
pause();
printf("interrupted after writing %zd bytes\n", write(fd, x, sizeof(x)));
close(fd);
kill(child, SIGTERM);
return 0;
}
Result before: "interrupted after writing 2147479552 bytes"
Result after: "interrupted after writing 4096 bytes"
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-22 22:25:41 +02:00
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2005-04-16 15:20:36 -07:00
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2022-05-19 17:31:36 -06:00
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2022-03-22 09:17:20 -07:00
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random: opportunistically initialize on /dev/urandom reads
In 6f98a4bfee72 ("random: block in /dev/urandom"), we tried to make a
successful try_to_generate_entropy() call *required* if the RNG was not
already initialized. Unfortunately, weird architectures and old
userspaces combined in TCG test harnesses, making that change still not
realistic, so it was reverted in 0313bc278dac ("Revert "random: block in
/dev/urandom"").
However, rather than making a successful try_to_generate_entropy() call
*required*, we can instead make it *best-effort*.
If try_to_generate_entropy() fails, it fails, and nothing changes from
the current behavior. If it succeeds, then /dev/urandom becomes safe to
use for free. This way, we don't risk the regression potential that led
to us reverting the required-try_to_generate_entropy() call before.
Practically speaking, this means that at least on x86, /dev/urandom
becomes safe. Probably other architectures with working cycle counters
will also become safe. And architectures with slow or broken cycle
counters at least won't be affected at all by this change.
So it may not be the glorious "all things are unified!" change we were
hoping for initially, but practically speaking, it makes a positive
impact.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-05 15:57:05 +02:00
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random: remove ratelimiting for in-kernel unseeded randomness
The CONFIG_WARN_ALL_UNSEEDED_RANDOM debug option controls whether the
kernel warns about all unseeded randomness or just the first instance.
There's some complicated rate limiting and comparison to the previous
caller, such that even with CONFIG_WARN_ALL_UNSEEDED_RANDOM enabled,
developers still don't see all the messages or even an accurate count of
how many were missed. This is the result of basically parallel
mechanisms aimed at accomplishing more or less the same thing, added at
different points in random.c history, which sort of compete with the
first-instance-only limiting we have now.
It turns out, however, that nobody cares about the first unseeded
randomness instance of in-kernel users. The same first user has been
there for ages now, and nobody is doing anything about it. It isn't even
clear that anybody _can_ do anything about it. Most places that can do
something about it have switched over to using get_random_bytes_wait()
or wait_for_random_bytes(), which is the right thing to do, but there is
still much code that needs randomness sometimes during init, and as a
geeneral rule, if you're not using one of the _wait functions or the
readiness notifier callback, you're bound to be doing it wrong just
based on that fact alone.
So warning about this same first user that can't easily change is simply
not an effective mechanism for anything at all. Users can't do anything
about it, as the Kconfig text points out -- the problem isn't in
userspace code -- and kernel developers don't or more often can't react
to it.
Instead, show the warning for all instances when CONFIG_WARN_ALL_UNSEEDED_RANDOM
is set, so that developers can debug things need be, or if it isn't set,
don't show a warning at all.
At the same time, CONFIG_WARN_ALL_UNSEEDED_RANDOM now implies setting
random.ratelimit_disable=1 on by default, since if you care about one
you probably care about the other too. And we can clean up usage around
the related urandom_warning ratelimiter as well (whose behavior isn't
changing), so that it properly counts missed messages after the 10
message threshold is reached.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-09 16:13:18 +02:00
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2022-05-19 17:31:36 -06:00
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random: remove ratelimiting for in-kernel unseeded randomness
The CONFIG_WARN_ALL_UNSEEDED_RANDOM debug option controls whether the
kernel warns about all unseeded randomness or just the first instance.
There's some complicated rate limiting and comparison to the previous
caller, such that even with CONFIG_WARN_ALL_UNSEEDED_RANDOM enabled,
developers still don't see all the messages or even an accurate count of
how many were missed. This is the result of basically parallel
mechanisms aimed at accomplishing more or less the same thing, added at
different points in random.c history, which sort of compete with the
first-instance-only limiting we have now.
It turns out, however, that nobody cares about the first unseeded
randomness instance of in-kernel users. The same first user has been
there for ages now, and nobody is doing anything about it. It isn't even
clear that anybody _can_ do anything about it. Most places that can do
something about it have switched over to using get_random_bytes_wait()
or wait_for_random_bytes(), which is the right thing to do, but there is
still much code that needs randomness sometimes during init, and as a
geeneral rule, if you're not using one of the _wait functions or the
readiness notifier callback, you're bound to be doing it wrong just
based on that fact alone.
So warning about this same first user that can't easily change is simply
not an effective mechanism for anything at all. Users can't do anything
about it, as the Kconfig text points out -- the problem isn't in
userspace code -- and kernel developers don't or more often can't react
to it.
Instead, show the warning for all instances when CONFIG_WARN_ALL_UNSEEDED_RANDOM
is set, so that developers can debug things need be, or if it isn't set,
don't show a warning at all.
At the same time, CONFIG_WARN_ALL_UNSEEDED_RANDOM now implies setting
random.ratelimit_disable=1 on by default, since if you care about one
you probably care about the other too. And we can clean up usage around
the related urandom_warning ratelimiter as well (whose behavior isn't
changing), so that it properly counts missed messages after the 10
message threshold is reached.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-09 16:13:18 +02:00
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2022-03-22 09:17:20 -07:00
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2022-05-19 17:31:36 -06:00
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2022-03-22 09:17:20 -07:00
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2022-05-19 17:31:36 -06:00
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2022-02-11 12:53:34 +01:00
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random: restore O_NONBLOCK support
Prior to 5.6, when /dev/random was opened with O_NONBLOCK, it would
return -EAGAIN if there was no entropy. When the pools were unified in
5.6, this was lost. The post 5.6 behavior of blocking until the pool is
initialized, and ignoring O_NONBLOCK in the process, went unnoticed,
with no reports about the regression received for two and a half years.
However, eventually this indeed did break somebody's userspace.
So we restore the old behavior, by returning -EAGAIN if the pool is not
initialized. Unlike the old /dev/random, this can only occur during
early boot, after which it never blocks again.
In order to make this O_NONBLOCK behavior consistent with other
expectations, also respect users reading with preadv2(RWF_NOWAIT) and
similar.
Fixes: 30c08efec888 ("random: make /dev/random be almost like /dev/urandom")
Reported-by: Guozihua <guozihua@huawei.com>
Reported-by: Zhongguohua <zhongguohua1@huawei.com>
Cc: Al Viro <viro@zeniv.linux.org.uk>
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Andrew Lutomirski <luto@kernel.org>
Cc: stable@vger.kernel.org
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-09-08 16:14:00 +02:00
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2022-02-11 12:53:34 +01:00
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2022-05-19 17:31:36 -06:00
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2022-02-11 12:53:34 +01:00
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2008-04-29 01:02:58 -07:00
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2005-04-16 15:20:36 -07:00
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2022-05-19 17:43:15 -06:00
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2005-04-16 15:20:36 -07:00
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2022-02-11 12:53:34 +01:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2005-04-16 15:20:36 -07:00
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2022-02-04 01:45:53 +01:00
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|
random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2022-02-04 01:45:53 +01:00
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2022-05-19 17:43:15 -06:00
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2005-04-16 15:20:36 -07:00
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2022-05-19 17:43:15 -06:00
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2022-09-15 20:25:47 -04:00
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2022-05-19 17:43:15 -06:00
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random: check for signals after page of pool writes
get_random_bytes_user() checks for signals after producing a PAGE_SIZE
worth of output, just like /dev/zero does. write_pool() is doing
basically the same work (actually, slightly more expensive), and so
should stop to check for signals in the same way. Let's also name it
write_pool_user() to match get_random_bytes_user(), so this won't be
misused in the future.
Before this patch, massive writes to /dev/urandom would tie up the
process for an extremely long time and make it unterminatable. After, it
can be successfully interrupted. The following test program can be used
to see this works as intended:
#include <unistd.h>
#include <fcntl.h>
#include <signal.h>
#include <stdio.h>
static unsigned char x[~0U];
static void handle(int) { }
int main(int argc, char *argv[])
{
pid_t pid = getpid(), child;
int fd;
signal(SIGUSR1, handle);
if (!(child = fork())) {
for (;;)
kill(pid, SIGUSR1);
}
fd = open("/dev/urandom", O_WRONLY);
pause();
printf("interrupted after writing %zd bytes\n", write(fd, x, sizeof(x)));
close(fd);
kill(child, SIGTERM);
return 0;
}
Result before: "interrupted after writing 2147479552 bytes"
Result after: "interrupted after writing 4096 bytes"
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-05-22 22:25:41 +02:00
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2022-05-19 17:43:15 -06:00
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2005-04-16 15:20:36 -07:00
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|
random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
|
|
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|
2022-02-04 01:45:53 +01:00
|
|
|
|
2022-05-19 17:43:15 -06:00
|
|
|
|
2005-04-16 15:20:36 -07:00
|
|
|
|
|
|
|
|
|
random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
|
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|
2005-04-16 15:20:36 -07:00
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2018-04-11 16:32:17 -04:00
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2022-03-08 11:20:17 -07:00
|
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|
2018-04-11 16:32:17 -04:00
|
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|
2022-11-17 17:47:12 +01:00
|
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|
2018-04-11 16:32:17 -04:00
|
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|
2005-04-16 15:20:36 -07:00
|
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|
random: add async notification support to /dev/random
Add async notification support to /dev/random.
A little test case is below. Without this patch, you get:
$ ./async-random
Drained the pool
Found more randomness
With it, you get:
$ ./async-random
Drained the pool
SIGIO
Found more randomness
#include <stdio.h>
#include <stdlib.h>
#include <signal.h>
#include <errno.h>
#include <fcntl.h>
static void handler(int sig)
{
printf("SIGIO\n");
}
int main(int argc, char **argv)
{
int fd, n, err, flags;
if(signal(SIGIO, handler) < 0){
perror("setting SIGIO handler");
exit(1);
}
fd = open("/dev/random", O_RDONLY);
if(fd < 0){
perror("open");
exit(1);
}
flags = fcntl(fd, F_GETFL);
if (flags < 0){
perror("getting flags");
exit(1);
}
flags |= O_NONBLOCK;
if (fcntl(fd, F_SETFL, flags) < 0){
perror("setting flags");
exit(1);
}
while((err = read(fd, &n, sizeof(n))) > 0) ;
if(err == 0){
printf("random returned 0\n");
exit(1);
}
else if(errno != EAGAIN){
perror("read");
exit(1);
}
flags |= O_ASYNC;
if (fcntl(fd, F_SETFL, flags) < 0){
perror("setting flags");
exit(1);
}
if (fcntl(fd, F_SETOWN, getpid()) < 0) {
perror("Setting SIGIO");
exit(1);
}
printf("Drained the pool\n");
read(fd, &n, sizeof(n));
printf("Found more randomness\n");
return(0);
}
Signed-off-by: Jeff Dike <jdike@linux.intel.com>
Signed-off-by: Matt Mackall <mpm@selenic.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2008-04-29 01:03:08 -07:00
|
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2007-02-12 00:55:32 -08:00
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|
2022-05-19 17:31:36 -06:00
|
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|
2022-05-19 17:43:15 -06:00
|
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|
2022-01-15 14:57:22 +01:00
|
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|
2008-04-29 01:02:58 -07:00
|
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|
|
2018-09-07 11:10:23 +02:00
|
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|
|
random: add async notification support to /dev/random
Add async notification support to /dev/random.
A little test case is below. Without this patch, you get:
$ ./async-random
Drained the pool
Found more randomness
With it, you get:
$ ./async-random
Drained the pool
SIGIO
Found more randomness
#include <stdio.h>
#include <stdlib.h>
#include <signal.h>
#include <errno.h>
#include <fcntl.h>
static void handler(int sig)
{
printf("SIGIO\n");
}
int main(int argc, char **argv)
{
int fd, n, err, flags;
if(signal(SIGIO, handler) < 0){
perror("setting SIGIO handler");
exit(1);
}
fd = open("/dev/random", O_RDONLY);
if(fd < 0){
perror("open");
exit(1);
}
flags = fcntl(fd, F_GETFL);
if (flags < 0){
perror("getting flags");
exit(1);
}
flags |= O_NONBLOCK;
if (fcntl(fd, F_SETFL, flags) < 0){
perror("setting flags");
exit(1);
}
while((err = read(fd, &n, sizeof(n))) > 0) ;
if(err == 0){
printf("random returned 0\n");
exit(1);
}
else if(errno != EAGAIN){
perror("read");
exit(1);
}
flags |= O_ASYNC;
if (fcntl(fd, F_SETFL, flags) < 0){
perror("setting flags");
exit(1);
}
if (fcntl(fd, F_SETOWN, getpid()) < 0) {
perror("Setting SIGIO");
exit(1);
}
printf("Drained the pool\n");
read(fd, &n, sizeof(n));
printf("Found more randomness\n");
return(0);
}
Signed-off-by: Jeff Dike <jdike@linux.intel.com>
Signed-off-by: Matt Mackall <mpm@selenic.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2008-04-29 01:03:08 -07:00
|
|
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|
llseek: automatically add .llseek fop
All file_operations should get a .llseek operation so we can make
nonseekable_open the default for future file operations without a
.llseek pointer.
The three cases that we can automatically detect are no_llseek, seq_lseek
and default_llseek. For cases where we can we can automatically prove that
the file offset is always ignored, we use noop_llseek, which maintains
the current behavior of not returning an error from a seek.
New drivers should normally not use noop_llseek but instead use no_llseek
and call nonseekable_open at open time. Existing drivers can be converted
to do the same when the maintainer knows for certain that no user code
relies on calling seek on the device file.
The generated code is often incorrectly indented and right now contains
comments that clarify for each added line why a specific variant was
chosen. In the version that gets submitted upstream, the comments will
be gone and I will manually fix the indentation, because there does not
seem to be a way to do that using coccinelle.
Some amount of new code is currently sitting in linux-next that should get
the same modifications, which I will do at the end of the merge window.
Many thanks to Julia Lawall for helping me learn to write a semantic
patch that does all this.
===== begin semantic patch =====
// This adds an llseek= method to all file operations,
// as a preparation for making no_llseek the default.
//
// The rules are
// - use no_llseek explicitly if we do nonseekable_open
// - use seq_lseek for sequential files
// - use default_llseek if we know we access f_pos
// - use noop_llseek if we know we don't access f_pos,
// but we still want to allow users to call lseek
//
@ open1 exists @
identifier nested_open;
@@
nested_open(...)
{
<+...
nonseekable_open(...)
...+>
}
@ open exists@
identifier open_f;
identifier i, f;
identifier open1.nested_open;
@@
int open_f(struct inode *i, struct file *f)
{
<+...
(
nonseekable_open(...)
|
nested_open(...)
)
...+>
}
@ read disable optional_qualifier exists @
identifier read_f;
identifier f, p, s, off;
type ssize_t, size_t, loff_t;
expression E;
identifier func;
@@
ssize_t read_f(struct file *f, char *p, size_t s, loff_t *off)
{
<+...
(
*off = E
|
*off += E
|
func(..., off, ...)
|
E = *off
)
...+>
}
@ read_no_fpos disable optional_qualifier exists @
identifier read_f;
identifier f, p, s, off;
type ssize_t, size_t, loff_t;
@@
ssize_t read_f(struct file *f, char *p, size_t s, loff_t *off)
{
... when != off
}
@ write @
identifier write_f;
identifier f, p, s, off;
type ssize_t, size_t, loff_t;
expression E;
identifier func;
@@
ssize_t write_f(struct file *f, const char *p, size_t s, loff_t *off)
{
<+...
(
*off = E
|
*off += E
|
func(..., off, ...)
|
E = *off
)
...+>
}
@ write_no_fpos @
identifier write_f;
identifier f, p, s, off;
type ssize_t, size_t, loff_t;
@@
ssize_t write_f(struct file *f, const char *p, size_t s, loff_t *off)
{
... when != off
}
@ fops0 @
identifier fops;
@@
struct file_operations fops = {
...
};
@ has_llseek depends on fops0 @
identifier fops0.fops;
identifier llseek_f;
@@
struct file_operations fops = {
...
.llseek = llseek_f,
...
};
@ has_read depends on fops0 @
identifier fops0.fops;
identifier read_f;
@@
struct file_operations fops = {
...
.read = read_f,
...
};
@ has_write depends on fops0 @
identifier fops0.fops;
identifier write_f;
@@
struct file_operations fops = {
...
.write = write_f,
...
};
@ has_open depends on fops0 @
identifier fops0.fops;
identifier open_f;
@@
struct file_operations fops = {
...
.open = open_f,
...
};
// use no_llseek if we call nonseekable_open
////////////////////////////////////////////
@ nonseekable1 depends on !has_llseek && has_open @
identifier fops0.fops;
identifier nso ~= "nonseekable_open";
@@
struct file_operations fops = {
... .open = nso, ...
+.llseek = no_llseek, /* nonseekable */
};
@ nonseekable2 depends on !has_llseek @
identifier fops0.fops;
identifier open.open_f;
@@
struct file_operations fops = {
... .open = open_f, ...
+.llseek = no_llseek, /* open uses nonseekable */
};
// use seq_lseek for sequential files
/////////////////////////////////////
@ seq depends on !has_llseek @
identifier fops0.fops;
identifier sr ~= "seq_read";
@@
struct file_operations fops = {
... .read = sr, ...
+.llseek = seq_lseek, /* we have seq_read */
};
// use default_llseek if there is a readdir
///////////////////////////////////////////
@ fops1 depends on !has_llseek && !nonseekable1 && !nonseekable2 && !seq @
identifier fops0.fops;
identifier readdir_e;
@@
// any other fop is used that changes pos
struct file_operations fops = {
... .readdir = readdir_e, ...
+.llseek = default_llseek, /* readdir is present */
};
// use default_llseek if at least one of read/write touches f_pos
/////////////////////////////////////////////////////////////////
@ fops2 depends on !fops1 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @
identifier fops0.fops;
identifier read.read_f;
@@
// read fops use offset
struct file_operations fops = {
... .read = read_f, ...
+.llseek = default_llseek, /* read accesses f_pos */
};
@ fops3 depends on !fops1 && !fops2 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @
identifier fops0.fops;
identifier write.write_f;
@@
// write fops use offset
struct file_operations fops = {
... .write = write_f, ...
+ .llseek = default_llseek, /* write accesses f_pos */
};
// Use noop_llseek if neither read nor write accesses f_pos
///////////////////////////////////////////////////////////
@ fops4 depends on !fops1 && !fops2 && !fops3 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @
identifier fops0.fops;
identifier read_no_fpos.read_f;
identifier write_no_fpos.write_f;
@@
// write fops use offset
struct file_operations fops = {
...
.write = write_f,
.read = read_f,
...
+.llseek = noop_llseek, /* read and write both use no f_pos */
};
@ depends on has_write && !has_read && !fops1 && !fops2 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @
identifier fops0.fops;
identifier write_no_fpos.write_f;
@@
struct file_operations fops = {
... .write = write_f, ...
+.llseek = noop_llseek, /* write uses no f_pos */
};
@ depends on has_read && !has_write && !fops1 && !fops2 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @
identifier fops0.fops;
identifier read_no_fpos.read_f;
@@
struct file_operations fops = {
... .read = read_f, ...
+.llseek = noop_llseek, /* read uses no f_pos */
};
@ depends on !has_read && !has_write && !fops1 && !fops2 && !has_llseek && !nonseekable1 && !nonseekable2 && !seq @
identifier fops0.fops;
@@
struct file_operations fops = {
...
+.llseek = noop_llseek, /* no read or write fn */
};
===== End semantic patch =====
Signed-off-by: Arnd Bergmann <arnd@arndb.de>
Cc: Julia Lawall <julia@diku.dk>
Cc: Christoph Hellwig <hch@infradead.org>
2010-08-15 18:52:59 +02:00
|
|
|
|
2023-05-22 14:49:59 +01:00
|
|
|
|
2022-05-19 17:31:37 -06:00
|
|
|
|
2005-04-16 15:20:36 -07:00
|
|
|
|
|
|
|
|
|
2022-03-22 09:17:20 -07:00
|
|
|
|
2022-05-19 17:31:36 -06:00
|
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|
|
2022-05-19 17:43:15 -06:00
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2022-03-22 09:17:20 -07:00
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2023-05-22 14:49:59 +01:00
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2022-05-19 17:31:37 -06:00
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2022-03-22 09:17:20 -07:00
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2022-02-11 12:53:34 +01:00
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2005-04-16 15:20:36 -07:00
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2022-02-11 12:53:34 +01:00
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2022-05-08 13:20:30 +02:00
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2022-02-11 12:53:34 +01:00
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2022-02-28 13:57:57 +01:00
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2022-02-11 12:53:34 +01:00
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2005-04-16 15:20:36 -07:00
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2022-02-28 13:57:57 +01:00
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2022-05-08 13:20:30 +02:00
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2022-02-05 14:00:58 +01:00
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2022-02-24 23:04:56 +01:00
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2005-04-16 15:20:36 -07:00
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2013-11-29 14:58:16 -05:00
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2022-02-24 23:04:56 +01:00
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2005-04-16 15:20:36 -07:00
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2022-05-13 13:18:46 +02:00
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2022-01-15 14:57:22 +01:00
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2005-04-16 15:20:36 -07:00
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2022-02-24 23:04:56 +01:00
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2005-04-16 15:20:36 -07:00
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2012-04-12 12:49:12 -07:00
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2005-04-16 15:20:36 -07:00
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2022-02-24 23:04:56 +01:00
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2022-05-13 13:18:46 +02:00
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2005-04-16 15:20:36 -07:00
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2022-02-28 14:00:52 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-28 14:00:52 +01:00
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2022-05-13 13:18:46 +02:00
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2022-02-28 14:00:52 +01:00
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2022-01-21 22:12:18 -08:00
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2005-04-16 15:20:36 -07:00
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2009-11-16 03:11:48 -08:00
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2005-04-16 15:20:36 -07:00
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random: do not pretend to handle premature next security model
Per the thread linked below, "premature next" is not considered to be a
realistic threat model, and leads to more serious security problems.
"Premature next" is the scenario in which:
- Attacker compromises the current state of a fully initialized RNG via
some kind of infoleak.
- New bits of entropy are added directly to the key used to generate the
/dev/urandom stream, without any buffering or pooling.
- Attacker then, somehow having read access to /dev/urandom, samples RNG
output and brute forces the individual new bits that were added.
- Result: the RNG never "recovers" from the initial compromise, a
so-called violation of what academics term "post-compromise security".
The usual solutions to this involve some form of delaying when entropy
gets mixed into the crng. With Fortuna, this involves multiple input
buckets. With what the Linux RNG was trying to do prior, this involves
entropy estimation.
However, by delaying when entropy gets mixed in, it also means that RNG
compromises are extremely dangerous during the window of time before
the RNG has gathered enough entropy, during which time nonces may become
predictable (or repeated), ephemeral keys may not be secret, and so
forth. Moreover, it's unclear how realistic "premature next" is from an
attack perspective, if these attacks even make sense in practice.
Put together -- and discussed in more detail in the thread below --
these constitute grounds for just doing away with the current code that
pretends to handle premature next. I say "pretends" because it wasn't
doing an especially great job at it either; should we change our mind
about this direction, we would probably implement Fortuna to "fix" the
"problem", in which case, removing the pretend solution still makes
sense.
This also reduces the crng reseed period from 5 minutes down to 1
minute. The rationale from the thread might lead us toward reducing that
even further in the future (or even eliminating it), but that remains a
topic of a future commit.
At a high level, this patch changes semantics from:
Before: Seed for the first time after 256 "bits" of estimated
entropy have been accumulated since the system booted. Thereafter,
reseed once every five minutes, but only if 256 new "bits" have been
accumulated since the last reseeding.
After: Seed for the first time after 256 "bits" of estimated entropy
have been accumulated since the system booted. Thereafter, reseed
once every minute.
Most of this patch is renaming and removing: POOL_MIN_BITS becomes
POOL_INIT_BITS, credit_entropy_bits() becomes credit_init_bits(),
crng_reseed() loses its "force" parameter since it's now always true,
the drain_entropy() function no longer has any use so it's removed,
entropy estimation is skipped if we've already init'd, the various
notifiers for "low on entropy" are now only active prior to init, and
finally, some documentation comments are cleaned up here and there.
Link: https://lore.kernel.org/lkml/YmlMGx6+uigkGiZ0@zx2c4.com/
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Nadia Heninger <nadiah@cs.ucsd.edu>
Cc: Tom Ristenpart <ristenpart@cornell.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-30 22:03:29 +02:00
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2005-04-16 15:20:36 -07:00
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random: use linear min-entropy accumulation crediting
30e37ec516ae ("random: account for entropy loss due to overwrites")
assumed that adding new entropy to the LFSR pool probabilistically
cancelled out old entropy there, so entropy was credited asymptotically,
approximating Shannon entropy of independent sources (rather than a
stronger min-entropy notion) using 1/8th fractional bits and replacing
a constant 2-2/√𝑒 term (~0.786938) with 3/4 (0.75) to slightly
underestimate it. This wasn't superb, but it was perhaps better than
nothing, so that's what was done. Which entropy specifically was being
cancelled out and how much precisely each time is hard to tell, though
as I showed with the attack code in my previous commit, a motivated
adversary with sufficient information can actually cancel out
everything.
Since we're no longer using an LFSR for entropy accumulation, this
probabilistic cancellation is no longer relevant. Rather, we're now
using a computational hash function as the accumulator and we've
switched to working in the random oracle model, from which we can now
revisit the question of min-entropy accumulation, which is done in
detail in <https://eprint.iacr.org/2019/198>.
Consider a long input bit string that is built by concatenating various
smaller independent input bit strings. Each one of these inputs has a
designated min-entropy, which is what we're passing to
credit_entropy_bits(h). When we pass the concatenation of these to a
random oracle, it means that an adversary trying to receive back the
same reply as us would need to become certain about each part of the
concatenated bit string we passed in, which means becoming certain about
all of those h values. That means we can estimate the accumulation by
simply adding up the h values in calls to credit_entropy_bits(h);
there's no probabilistic cancellation at play like there was said to be
for the LFSR. Incidentally, this is also what other entropy accumulators
based on computational hash functions do as well.
So this commit replaces credit_entropy_bits(h) with essentially `total =
min(POOL_BITS, total + h)`, done with a cmpxchg loop as before.
What if we're wrong and the above is nonsense? It's not, but let's
assume we don't want the actual _behavior_ of the code to change much.
Currently that behavior is not extracting from the input pool until it
has 128 bits of entropy in it. With the old algorithm, we'd hit that
magic 128 number after roughly 256 calls to credit_entropy_bits(1). So,
we can retain more or less the old behavior by waiting to extract from
the input pool until it hits 256 bits of entropy using the new code. For
people concerned about this change, it means that there's not that much
practical behavioral change. And for folks actually trying to model
the behavior rigorously, it means that we have an even higher margin
against attacks.
Cc: Theodore Ts'o <tytso@mit.edu>
Cc: Dominik Brodowski <linux@dominikbrodowski.net>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Reviewed-by: Jean-Philippe Aumasson <jeanphilippe.aumasson@gmail.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-03 13:28:06 +01:00
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2005-04-16 15:20:36 -07:00
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2022-02-11 12:53:34 +01:00
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2005-04-16 15:20:36 -07:00
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2022-02-28 14:00:52 +01:00
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2005-04-16 15:20:36 -07:00
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2013-09-22 15:14:32 -04:00
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2022-02-11 12:53:34 +01:00
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2013-09-22 15:14:32 -04:00
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2022-02-28 14:00:52 +01:00
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2013-09-22 15:14:32 -04:00
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2005-04-16 15:20:36 -07:00
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2009-11-16 03:11:48 -08:00
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2005-04-16 15:20:36 -07:00
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2009-11-16 03:11:48 -08:00
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2005-04-16 15:20:36 -07:00
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2022-01-21 22:12:18 -08:00
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2022-05-05 02:20:22 +02:00
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2022-01-21 22:12:18 -08:00
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2022-02-11 12:53:34 +01:00
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