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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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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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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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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2016-06-12 18:13:36 -04:00
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2018-04-11 13:27:52 -04:00
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2022-02-11 12:53:34 +01:00
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2022-03-01 20:03:49 +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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2018-04-25 01:12:32 -04:00
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2022-03-22 09:17:20 -07:00
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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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2022-02-11 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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2022-03-08 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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2022-03-01 20:03:49 +01:00
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2022-02-11 12:53:34 +01:00
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2022-03-01 20:03:49 +01:00
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2022-02-11 12:53:34 +01:00
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2022-03-01 20:03:49 +01:00
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2022-02-11 12:53:34 +01:00
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2022-03-01 20:03:49 +01:00
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2022-02-11 12:53:34 +01:00
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2022-03-01 20:03:49 +01:00
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2022-02-11 12:53:34 +01:00
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2022-03-01 20:03:49 +01:00
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2022-02-11 12:53:34 +01:00
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2022-03-01 20:03:49 +01:00
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2022-02-11 12:53:34 +01:00
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2022-03-01 20:03:49 +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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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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2022-03-22 09:17:20 -07:00
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2022-03-22 22:21:52 -06:00
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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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2016-06-12 18:13:36 -04:00
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2022-02-11 12:53:34 +01:00
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2022-02-23 13:43:44 +01:00
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2016-06-12 18:13:36 -04:00
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2018-04-11 14:58:27 -04:00
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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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2018-04-11 14:58:27 -04:00
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2022-02-23 13:43:44 +01:00
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2016-06-12 18:13:36 -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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2022-02-09 19:57:06 +01:00
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2016-06-12 18:13:36 -04:00
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2022-02-11 12:19:49 +01:00
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2022-02-23 13:43:44 +01:00
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2022-02-11 12:19:49 +01:00
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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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2022-03-08 11:20:17 -07:00
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2022-02-06 23:51:41 +01:00
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2022-02-09 19:57:06 +01:00
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2022-02-06 23:51:41 +01:00
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2022-03-22 09:17:20 -07:00
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2022-02-06 23:51:41 +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
|
|
|
|
2022-02-11 12:53:34 +01:00
|
|
|
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|
|
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|
|
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|
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|
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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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|
|
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|
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|
|
|
2016-06-12 18:13:36 -04:00
|
|
|
|
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
|
|
|
|
2021-12-20 16:41:57 -06:00
|
|
|
|
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 memmove instead of memcpy for remaining 32 bytes
In order to immediately overwrite the old key on the stack, before
servicing a userspace request for bytes, we use the remaining 32 bytes
of block 0 as the key. This means moving indices 8,9,a,b,c,d,e,f ->
4,5,6,7,8,9,a,b. Since 4 < 8, for the kernel implementations of
memcpy(), this doesn't actually appear to be a problem in practice. But
relying on that characteristic seems a bit brittle. So let's change that
to a proper memmove(), which is the by-the-books way of handling
overlapping memory copies.
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-04-14 01:50:38 +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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random: reseed more often immediately after booting
In order to chip away at the "premature first" problem, we augment our
existing entropy accounting with more frequent reseedings at boot.
The idea is that at boot, we're getting entropy from various places, and
we're not very sure which of early boot entropy is good and which isn't.
Even when we're crediting the entropy, we're still not totally certain
that it's any good. Since boot is the one time (aside from a compromise)
that we have zero entropy, it's important that we shepherd entropy into
the crng fairly often.
At the same time, we don't want a "premature next" problem, whereby an
attacker can brute force individual bits of added entropy. In lieu of
going full-on Fortuna (for now), we can pick a simpler strategy of just
reseeding more often during the first 5 minutes after boot. This is
still bounded by the 256-bit entropy credit requirement, so we'll skip a
reseeding if we haven't reached that, but in case entropy /is/ coming
in, this ensures that it makes its way into the crng rather rapidly
during these early stages.
Ordinarily we reseed if the previous reseeding is 300 seconds old. This
commit changes things so that for the first 600 seconds of boot time, we
reseed if the previous reseeding is uptime / 2 seconds old. That means
that we'll reseed at the very least double the uptime of the previous
reseeding.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-08 23:32:34 -07:00
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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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2022-02-12 23:54:09 +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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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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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: reseed more often immediately after booting
In order to chip away at the "premature first" problem, we augment our
existing entropy accounting with more frequent reseedings at boot.
The idea is that at boot, we're getting entropy from various places, and
we're not very sure which of early boot entropy is good and which isn't.
Even when we're crediting the entropy, we're still not totally certain
that it's any good. Since boot is the one time (aside from a compromise)
that we have zero entropy, it's important that we shepherd entropy into
the crng fairly often.
At the same time, we don't want a "premature next" problem, whereby an
attacker can brute force individual bits of added entropy. In lieu of
going full-on Fortuna (for now), we can pick a simpler strategy of just
reseeding more often during the first 5 minutes after boot. This is
still bounded by the 256-bit entropy credit requirement, so we'll skip a
reseeding if we haven't reached that, but in case entropy /is/ coming
in, this ensures that it makes its way into the crng rather rapidly
during these early stages.
Ordinarily we reseed if the previous reseeding is 300 seconds old. This
commit changes things so that for the first 600 seconds of boot time, we
reseed if the previous reseeding is uptime / 2 seconds old. That means
that we'll reseed at the very least double the uptime of the previous
reseeding.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-08 23:32:34 -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: reseed more often immediately after booting
In order to chip away at the "premature first" problem, we augment our
existing entropy accounting with more frequent reseedings at boot.
The idea is that at boot, we're getting entropy from various places, and
we're not very sure which of early boot entropy is good and which isn't.
Even when we're crediting the entropy, we're still not totally certain
that it's any good. Since boot is the one time (aside from a compromise)
that we have zero entropy, it's important that we shepherd entropy into
the crng fairly often.
At the same time, we don't want a "premature next" problem, whereby an
attacker can brute force individual bits of added entropy. In lieu of
going full-on Fortuna (for now), we can pick a simpler strategy of just
reseeding more often during the first 5 minutes after boot. This is
still bounded by the 256-bit entropy credit requirement, so we'll skip a
reseeding if we haven't reached that, but in case entropy /is/ coming
in, this ensures that it makes its way into the crng rather rapidly
during these early stages.
Ordinarily we reseed if the previous reseeding is 300 seconds old. This
commit changes things so that for the first 600 seconds of boot time, we
reseed if the previous reseeding is uptime / 2 seconds old. That means
that we'll reseed at the very least double the uptime of the previous
reseeding.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Eric Biggers <ebiggers@google.com>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-03-08 23:32:34 -07:00
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2022-02-23 13:43:44 +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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2022-02-11 12:53:34 +01:00
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2022-02-12 23:54:09 +01:00
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2022-02-11 12:53:34 +01:00
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2022-02-12 23:54:09 +01:00
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2022-02-11 12:53:34 +01:00
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2022-04-04 19:42:30 +03:00
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2022-02-11 12:53:34 +01:00
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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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2022-02-11 12:53:34 +01:00
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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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2022-02-12 23:54:09 +01:00
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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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2022-02-11 12:53:34 +01:00
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2022-04-04 19:42:30 +03:00
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2022-02-11 12:53:34 +01:00
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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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2022-02-11 12:53:34 +01:00
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2022-02-12 23:54:09 +01:00
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2022-04-04 19:42:30 +03:00
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2022-02-12 23:54:09 +01:00
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2022-02-11 12:53:34 +01:00
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2022-02-12 23:54:09 +01:00
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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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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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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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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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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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2022-02-11 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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2022-02-11 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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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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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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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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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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2022-02-11 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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2022-02-23 13:43:44 +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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2022-02-11 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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2022-02-11 12:53:34 +01:00
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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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2022-02-23 13:43:44 +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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2022-02-11 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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2022-02-23 13:43:44 +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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2022-02-23 13:43:44 +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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2022-02-23 13:43:44 +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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2022-03-22 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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2022-03-22 21:43:12 -06:00
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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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2022-02-11 12:53:34 +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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2022-03-31 11:01:01 -04:00
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2022-02-11 12:53:34 +01:00
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2022-02-12 01:26:17 +01:00
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2022-02-11 12:53:34 +01:00
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2022-02-12 01:26:17 +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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2022-02-11 12:53:34 +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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2022-03-08 11:20:17 -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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2022-03-22 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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2022-02-11 12:53:34 +01:00
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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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2016-06-12 18:13:36 -04:00
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2012-07-04 11:16:01 -04:00
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2022-02-09 14:43:25 +01:00
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2012-07-04 11:16:01 -04:00
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2022-04-08 18:14:57 +02:00
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random: unify cycles_t and jiffies usage and types
random_get_entropy() returns a cycles_t, not an unsigned long, which is
sometimes 64 bits on various 32-bit platforms, including x86.
Conversely, jiffies is always unsigned long. This commit fixes things to
use cycles_t for fields that use random_get_entropy(), named "cycles",
and unsigned long for fields that use jiffies, named "now". It's also
good to mix in a cycles_t and a jiffies in the same way for both
add_device_randomness and add_timer_randomness, rather than using xor in
one case. Finally, we unify the order of these volatile reads, always
reading the more precise cycles counter, and then jiffies, so that the
cycle counter is as close to the event as possible.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-24 18:30:58 +01:00
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2012-07-04 11:16:01 -04:00
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2022-02-12 23:57:38 +01:00
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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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2017-07-12 14:34:04 -07:00
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2013-09-12 14:27:22 -04:00
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|
random: unify cycles_t and jiffies usage and types
random_get_entropy() returns a cycles_t, not an unsigned long, which is
sometimes 64 bits on various 32-bit platforms, including x86.
Conversely, jiffies is always unsigned long. This commit fixes things to
use cycles_t for fields that use random_get_entropy(), named "cycles",
and unsigned long for fields that use jiffies, named "now". It's also
good to mix in a cycles_t and a jiffies in the same way for both
add_device_randomness and add_timer_randomness, rather than using xor in
one case. Finally, we unify the order of these volatile reads, always
reading the more precise cycles counter, and then jiffies, so that the
cycle counter is as close to the event as possible.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-24 18:30:58 +01:00
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2022-01-12 17:18:08 +01:00
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2013-09-12 14:27:22 -04:00
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2012-07-04 11:16:01 -04:00
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random: unify cycles_t and jiffies usage and types
random_get_entropy() returns a cycles_t, not an unsigned long, which is
sometimes 64 bits on various 32-bit platforms, including x86.
Conversely, jiffies is always unsigned long. This commit fixes things to
use cycles_t for fields that use random_get_entropy(), named "cycles",
and unsigned long for fields that use jiffies, named "now". It's also
good to mix in a cycles_t and a jiffies in the same way for both
add_device_randomness and add_timer_randomness, rather than using xor in
one case. Finally, we unify the order of these volatile reads, always
reading the more precise cycles counter, and then jiffies, so that the
cycle counter is as close to the event as possible.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-24 18:30:58 +01:00
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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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2005-04-16 15:20:36 -07:00
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2022-04-08 18:14:57 +02:00
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2005-04-16 15:20:36 -07:00
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random: unify cycles_t and jiffies usage and types
random_get_entropy() returns a cycles_t, not an unsigned long, which is
sometimes 64 bits on various 32-bit platforms, including x86.
Conversely, jiffies is always unsigned long. This commit fixes things to
use cycles_t for fields that use random_get_entropy(), named "cycles",
and unsigned long for fields that use jiffies, named "now". It's also
good to mix in a cycles_t and a jiffies in the same way for both
add_device_randomness and add_timer_randomness, rather than using xor in
one case. Finally, we unify the order of these volatile reads, always
reading the more precise cycles counter, and then jiffies, so that the
cycle counter is as close to the event as possible.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-24 18:30:58 +01:00
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2005-04-16 15:20:36 -07:00
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random: unify cycles_t and jiffies usage and types
random_get_entropy() returns a cycles_t, not an unsigned long, which is
sometimes 64 bits on various 32-bit platforms, including x86.
Conversely, jiffies is always unsigned long. This commit fixes things to
use cycles_t for fields that use random_get_entropy(), named "cycles",
and unsigned long for fields that use jiffies, named "now". It's also
good to mix in a cycles_t and a jiffies in the same way for both
add_device_randomness and add_timer_randomness, rather than using xor in
one case. Finally, we unify the order of these volatile reads, always
reading the more precise cycles counter, and then jiffies, so that the
cycle counter is as close to the event as possible.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-24 18:30:58 +01:00
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2018-03-01 00:22:47 +01:00
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2020-02-25 11:27:04 -05:00
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2018-03-01 00:22:47 +01:00
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2020-02-25 11:27:04 -05:00
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2018-03-01 00:22:47 +01:00
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2005-04-16 15:20:36 -07:00
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2018-03-01 00:22:47 +01:00
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2020-01-07 16:55:34 -05:00
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2018-03-01 00:22:47 +01:00
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2022-02-09 14:43:25 +01:00
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2005-04-16 15:20:36 -07:00
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2006-01-11 12:17:38 -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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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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2006-10-11 01:43:58 -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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2022-03-21 18:48:05 -06:00
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2022-04-04 19:42:30 +03:00
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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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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
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2022-03-01 20:22:39 +01:00
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2022-02-23 13:43:44 +01:00
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2022-03-01 20:22:39 +01:00
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2022-02-23 13:43:44 +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
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2022-02-23 13:43:44 +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
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2022-03-01 20:22:39 +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
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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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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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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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2022-02-11 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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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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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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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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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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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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2022-02-22 13:46:10 +01:00
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2014-06-15 16:59:24 -04:00
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2022-02-22 13:46:10 +01:00
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2017-06-07 19:01:32 -04:00
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2014-06-15 16:59:24 -04:00
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2017-06-07 19:01:32 -04:00
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2022-02-22 13:46:10 +01:00
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2017-06-07 19:01:32 -04:00
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2017-04-30 19:49:21 +12:00
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2014-06-15 16:59:24 -04:00
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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: 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: 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: 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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2022-04-08 18:14:57 +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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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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2008-08-19 20:50:08 -07:00
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2014-06-15 16:59:24 -04:00
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2008-08-19 20:50:08 -07:00
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2022-04-08 18:14:57 +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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2022-04-08 18:14:57 +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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2022-02-10 17:01:27 +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: 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: 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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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: 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: 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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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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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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2022-01-12 17:18:08 +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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2022-04-08 18:14:57 +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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random: unify cycles_t and jiffies usage and types
random_get_entropy() returns a cycles_t, not an unsigned long, which is
sometimes 64 bits on various 32-bit platforms, including x86.
Conversely, jiffies is always unsigned long. This commit fixes things to
use cycles_t for fields that use random_get_entropy(), named "cycles",
and unsigned long for fields that use jiffies, named "now". It's also
good to mix in a cycles_t and a jiffies in the same way for both
add_device_randomness and add_timer_randomness, rather than using xor in
one case. Finally, we unify the order of these volatile reads, always
reading the more precise cycles counter, and then jiffies, so that the
cycle counter is as close to the event as possible.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-24 18:30:58 +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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random: unify cycles_t and jiffies usage and types
random_get_entropy() returns a cycles_t, not an unsigned long, which is
sometimes 64 bits on various 32-bit platforms, including x86.
Conversely, jiffies is always unsigned long. This commit fixes things to
use cycles_t for fields that use random_get_entropy(), named "cycles",
and unsigned long for fields that use jiffies, named "now". It's also
good to mix in a cycles_t and a jiffies in the same way for both
add_device_randomness and add_timer_randomness, rather than using xor in
one case. Finally, we unify the order of these volatile reads, always
reading the more precise cycles counter, and then jiffies, so that the
cycle counter is as close to the event as possible.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-24 18:30:58 +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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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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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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2022-01-15 14:57:22 +01:00
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random: unify cycles_t and jiffies usage and types
random_get_entropy() returns a cycles_t, not an unsigned long, which is
sometimes 64 bits on various 32-bit platforms, including x86.
Conversely, jiffies is always unsigned long. This commit fixes things to
use cycles_t for fields that use random_get_entropy(), named "cycles",
and unsigned long for fields that use jiffies, named "now". It's also
good to mix in a cycles_t and a jiffies in the same way for both
add_device_randomness and add_timer_randomness, rather than using xor in
one case. Finally, we unify the order of these volatile reads, always
reading the more precise cycles counter, and then jiffies, so that the
cycle counter is as close to the event as possible.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-24 18:30:58 +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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random: unify cycles_t and jiffies usage and types
random_get_entropy() returns a cycles_t, not an unsigned long, which is
sometimes 64 bits on various 32-bit platforms, including x86.
Conversely, jiffies is always unsigned long. This commit fixes things to
use cycles_t for fields that use random_get_entropy(), named "cycles",
and unsigned long for fields that use jiffies, named "now". It's also
good to mix in a cycles_t and a jiffies in the same way for both
add_device_randomness and add_timer_randomness, rather than using xor in
one case. Finally, we unify the order of these volatile reads, always
reading the more precise cycles counter, and then jiffies, so that the
cycle counter is as close to the event as possible.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-24 18:30:58 +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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random: unify cycles_t and jiffies usage and types
random_get_entropy() returns a cycles_t, not an unsigned long, which is
sometimes 64 bits on various 32-bit platforms, including x86.
Conversely, jiffies is always unsigned long. This commit fixes things to
use cycles_t for fields that use random_get_entropy(), named "cycles",
and unsigned long for fields that use jiffies, named "now". It's also
good to mix in a cycles_t and a jiffies in the same way for both
add_device_randomness and add_timer_randomness, rather than using xor in
one case. Finally, we unify the order of these volatile reads, always
reading the more precise cycles counter, and then jiffies, so that the
cycle counter is as close to the event as possible.
Cc: Theodore Ts'o <tytso@mit.edu>
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
2022-02-24 18:30:58 +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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2005-04-16 15:20:36 -07:00
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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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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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2019-12-23 00:20:48 -08:00
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2022-02-11 12:53:34 +01:00
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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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2018-06-28 09:43:44 -07:00
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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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2018-06-28 09:43:44 -07:00
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2019-12-23 00:20:48 -08:00
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2018-02-11 14:34:03 -08:00
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2022-02-05 14:00:58 +01:00
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2018-02-11 14:34:03 -08:00
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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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2005-04-16 15:20:36 -07:00
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2022-02-09 14:43:25 +01:00
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2022-02-09 18:42:13 +01:00
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2022-02-09 14:43:25 +01:00
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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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2022-02-09 18:42:13 +01:00
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2022-02-09 14:43:25 +01:00
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2008-02-06 01:37:20 -08:00
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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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2007-05-29 21:58:10 -05:00
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2008-04-29 01:02:55 -07:00
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2007-05-29 21:58:10 -05:00
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2022-02-09 14:43:25 +01:00
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2007-05-29 21:58:10 -05:00
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2022-01-12 17:18:08 +01:00
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2007-05-29 21:58:10 -05:00
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2005-04-16 15:20:36 -07:00
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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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2022-03-22 09:17:20 -07:00
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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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2022-02-11 12:53:34 +01:00
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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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2022-02-04 01:45:53 +01:00
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2005-04-16 15:20:36 -07:00
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2022-01-12 17:18:08 +01:00
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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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2005-04-16 15:20:36 -07:00
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2013-11-03 07:56:17 -05:00
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2005-04-16 15:20:36 -07:00
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2022-02-22 14:01:57 +01:00
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2022-01-28 23:44:03 +01:00
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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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2022-02-23 13:43:44 +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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2022-01-15 14:57:22 +01:00
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2005-04-16 15:20:36 -07:00
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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
|
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|
2005-04-16 15:20:36 -07:00
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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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2022-02-28 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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2022-02-11 12:53:34 +01:00
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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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2022-01-15 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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2005-04-16 15:20:36 -07:00
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2022-02-28 14:00:52 +01:00
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2022-01-21 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: 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
|
|
|
|
2005-04-16 15:20:36 -07:00
|
|
|
|
|
|
|
|
|
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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2009-11-05 14:34:02 -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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2022-02-11 12:53:34 +01:00
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