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glibc/stdlib/arc4random_uniform.c

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stdlib: Add arc4random, arc4random_buf, and arc4random_uniform (BZ #4417) The implementation is based on scalar Chacha20 with per-thread cache. It uses getrandom or /dev/urandom as fallback to get the initial entropy, and reseeds the internal state on every 16MB of consumed buffer. To improve performance and lower memory consumption the per-thread cache is allocated lazily on first arc4random functions call, and if the memory allocation fails getentropy or /dev/urandom is used as fallback. The cache is also cleared on thread exit iff it was initialized (so if arc4random is not called it is not touched). Although it is lock-free, arc4random is still not async-signal-safe (the per thread state is not updated atomically). The ChaCha20 implementation is based on RFC8439 [1], omitting the final XOR of the keystream with the plaintext because the plaintext is a stream of zeros. This strategy is similar to what OpenBSD arc4random does. The arc4random_uniform is based on previous work by Florian Weimer, where the algorithm is based on Jérémie Lumbroso paper Optimal Discrete Uniform Generation from Coin Flips, and Applications (2013) [2], who credits Donald E. Knuth and Andrew C. Yao, The complexity of nonuniform random number generation (1976), for solving the general case. The main advantage of this method is the that the unit of randomness is not the uniform random variable (uint32_t), but a random bit. It optimizes the internal buffer sampling by initially consuming a 32-bit random variable and then sampling byte per byte. Depending of the upper bound requested, it might lead to better CPU utilization. Checked on x86_64-linux-gnu, aarch64-linux, and powerpc64le-linux-gnu. Co-authored-by: Florian Weimer <fweimer@redhat.com> Reviewed-by: Yann Droneaud <ydroneaud@opteya.com> [1] https://datatracker.ietf.org/doc/html/rfc8439 [2] https://arxiv.org/pdf/1304.1916.pdf
2022-07-21 13:04:59 +00:00
/* Random pseudo generator number which returns a single 32 bit value
uniformly distributed but with an upper_bound.
Copyright (C) 2022 Free Software Foundation, Inc.
This file is part of the GNU C Library.
The GNU C Library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
The GNU C Library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with the GNU C Library; if not, see
<https://www.gnu.org/licenses/>. */
#include <stdlib.h>
#include <sys/param.h>
stdlib: Simplify arc4random_uniform It uses the bitmask with rejection [1], which calculates a mask being the lowest power of two bounding the request upper bound, successively queries new random values, and rejects values outside the requested range. Performance-wise, there is no much gain in trying to conserve bits since arc4random is wrapper on getrandom syscall. It should be cheaper to just query a uint32_t value. The algorithm also avoids modulo and divide operations, which might be costly depending of the architecture. [1] https://www.pcg-random.org/posts/bounded-rands.html Reviewed-by: Yann Droneaud <ydroneaud@opteya.com>
2022-07-28 12:18:01 +00:00
/* Return a uniformly distributed random number less than N. The algorithm
calculates a mask being the lowest power of two bounding the upper bound
N, successively queries new random values, and rejects values outside of
the request range.
stdlib: Add arc4random, arc4random_buf, and arc4random_uniform (BZ #4417) The implementation is based on scalar Chacha20 with per-thread cache. It uses getrandom or /dev/urandom as fallback to get the initial entropy, and reseeds the internal state on every 16MB of consumed buffer. To improve performance and lower memory consumption the per-thread cache is allocated lazily on first arc4random functions call, and if the memory allocation fails getentropy or /dev/urandom is used as fallback. The cache is also cleared on thread exit iff it was initialized (so if arc4random is not called it is not touched). Although it is lock-free, arc4random is still not async-signal-safe (the per thread state is not updated atomically). The ChaCha20 implementation is based on RFC8439 [1], omitting the final XOR of the keystream with the plaintext because the plaintext is a stream of zeros. This strategy is similar to what OpenBSD arc4random does. The arc4random_uniform is based on previous work by Florian Weimer, where the algorithm is based on Jérémie Lumbroso paper Optimal Discrete Uniform Generation from Coin Flips, and Applications (2013) [2], who credits Donald E. Knuth and Andrew C. Yao, The complexity of nonuniform random number generation (1976), for solving the general case. The main advantage of this method is the that the unit of randomness is not the uniform random variable (uint32_t), but a random bit. It optimizes the internal buffer sampling by initially consuming a 32-bit random variable and then sampling byte per byte. Depending of the upper bound requested, it might lead to better CPU utilization. Checked on x86_64-linux-gnu, aarch64-linux, and powerpc64le-linux-gnu. Co-authored-by: Florian Weimer <fweimer@redhat.com> Reviewed-by: Yann Droneaud <ydroneaud@opteya.com> [1] https://datatracker.ietf.org/doc/html/rfc8439 [2] https://arxiv.org/pdf/1304.1916.pdf
2022-07-21 13:04:59 +00:00
stdlib: Simplify arc4random_uniform It uses the bitmask with rejection [1], which calculates a mask being the lowest power of two bounding the request upper bound, successively queries new random values, and rejects values outside the requested range. Performance-wise, there is no much gain in trying to conserve bits since arc4random is wrapper on getrandom syscall. It should be cheaper to just query a uint32_t value. The algorithm also avoids modulo and divide operations, which might be costly depending of the architecture. [1] https://www.pcg-random.org/posts/bounded-rands.html Reviewed-by: Yann Droneaud <ydroneaud@opteya.com>
2022-07-28 12:18:01 +00:00
For reject values, it also tries if the remaining entropy could fit on
the asked range after range adjustment.
stdlib: Add arc4random, arc4random_buf, and arc4random_uniform (BZ #4417) The implementation is based on scalar Chacha20 with per-thread cache. It uses getrandom or /dev/urandom as fallback to get the initial entropy, and reseeds the internal state on every 16MB of consumed buffer. To improve performance and lower memory consumption the per-thread cache is allocated lazily on first arc4random functions call, and if the memory allocation fails getentropy or /dev/urandom is used as fallback. The cache is also cleared on thread exit iff it was initialized (so if arc4random is not called it is not touched). Although it is lock-free, arc4random is still not async-signal-safe (the per thread state is not updated atomically). The ChaCha20 implementation is based on RFC8439 [1], omitting the final XOR of the keystream with the plaintext because the plaintext is a stream of zeros. This strategy is similar to what OpenBSD arc4random does. The arc4random_uniform is based on previous work by Florian Weimer, where the algorithm is based on Jérémie Lumbroso paper Optimal Discrete Uniform Generation from Coin Flips, and Applications (2013) [2], who credits Donald E. Knuth and Andrew C. Yao, The complexity of nonuniform random number generation (1976), for solving the general case. The main advantage of this method is the that the unit of randomness is not the uniform random variable (uint32_t), but a random bit. It optimizes the internal buffer sampling by initially consuming a 32-bit random variable and then sampling byte per byte. Depending of the upper bound requested, it might lead to better CPU utilization. Checked on x86_64-linux-gnu, aarch64-linux, and powerpc64le-linux-gnu. Co-authored-by: Florian Weimer <fweimer@redhat.com> Reviewed-by: Yann Droneaud <ydroneaud@opteya.com> [1] https://datatracker.ietf.org/doc/html/rfc8439 [2] https://arxiv.org/pdf/1304.1916.pdf
2022-07-21 13:04:59 +00:00
stdlib: Simplify arc4random_uniform It uses the bitmask with rejection [1], which calculates a mask being the lowest power of two bounding the request upper bound, successively queries new random values, and rejects values outside the requested range. Performance-wise, there is no much gain in trying to conserve bits since arc4random is wrapper on getrandom syscall. It should be cheaper to just query a uint32_t value. The algorithm also avoids modulo and divide operations, which might be costly depending of the architecture. [1] https://www.pcg-random.org/posts/bounded-rands.html Reviewed-by: Yann Droneaud <ydroneaud@opteya.com>
2022-07-28 12:18:01 +00:00
The algorithm avoids modulo and divide operations, which might be costly
depending on the architecture. */
stdlib: Add arc4random, arc4random_buf, and arc4random_uniform (BZ #4417) The implementation is based on scalar Chacha20 with per-thread cache. It uses getrandom or /dev/urandom as fallback to get the initial entropy, and reseeds the internal state on every 16MB of consumed buffer. To improve performance and lower memory consumption the per-thread cache is allocated lazily on first arc4random functions call, and if the memory allocation fails getentropy or /dev/urandom is used as fallback. The cache is also cleared on thread exit iff it was initialized (so if arc4random is not called it is not touched). Although it is lock-free, arc4random is still not async-signal-safe (the per thread state is not updated atomically). The ChaCha20 implementation is based on RFC8439 [1], omitting the final XOR of the keystream with the plaintext because the plaintext is a stream of zeros. This strategy is similar to what OpenBSD arc4random does. The arc4random_uniform is based on previous work by Florian Weimer, where the algorithm is based on Jérémie Lumbroso paper Optimal Discrete Uniform Generation from Coin Flips, and Applications (2013) [2], who credits Donald E. Knuth and Andrew C. Yao, The complexity of nonuniform random number generation (1976), for solving the general case. The main advantage of this method is the that the unit of randomness is not the uniform random variable (uint32_t), but a random bit. It optimizes the internal buffer sampling by initially consuming a 32-bit random variable and then sampling byte per byte. Depending of the upper bound requested, it might lead to better CPU utilization. Checked on x86_64-linux-gnu, aarch64-linux, and powerpc64le-linux-gnu. Co-authored-by: Florian Weimer <fweimer@redhat.com> Reviewed-by: Yann Droneaud <ydroneaud@opteya.com> [1] https://datatracker.ietf.org/doc/html/rfc8439 [2] https://arxiv.org/pdf/1304.1916.pdf
2022-07-21 13:04:59 +00:00
uint32_t
__arc4random_uniform (uint32_t n)
{
if (n <= 1)
/* There is no valid return value for a zero limit, and 0 is the
only possible result for limit 1. */
return 0;
/* Powers of two are easy. */
if (powerof2 (n))
stdlib: Simplify arc4random_uniform It uses the bitmask with rejection [1], which calculates a mask being the lowest power of two bounding the request upper bound, successively queries new random values, and rejects values outside the requested range. Performance-wise, there is no much gain in trying to conserve bits since arc4random is wrapper on getrandom syscall. It should be cheaper to just query a uint32_t value. The algorithm also avoids modulo and divide operations, which might be costly depending of the architecture. [1] https://www.pcg-random.org/posts/bounded-rands.html Reviewed-by: Yann Droneaud <ydroneaud@opteya.com>
2022-07-28 12:18:01 +00:00
return __arc4random () & (n - 1);
stdlib: Add arc4random, arc4random_buf, and arc4random_uniform (BZ #4417) The implementation is based on scalar Chacha20 with per-thread cache. It uses getrandom or /dev/urandom as fallback to get the initial entropy, and reseeds the internal state on every 16MB of consumed buffer. To improve performance and lower memory consumption the per-thread cache is allocated lazily on first arc4random functions call, and if the memory allocation fails getentropy or /dev/urandom is used as fallback. The cache is also cleared on thread exit iff it was initialized (so if arc4random is not called it is not touched). Although it is lock-free, arc4random is still not async-signal-safe (the per thread state is not updated atomically). The ChaCha20 implementation is based on RFC8439 [1], omitting the final XOR of the keystream with the plaintext because the plaintext is a stream of zeros. This strategy is similar to what OpenBSD arc4random does. The arc4random_uniform is based on previous work by Florian Weimer, where the algorithm is based on Jérémie Lumbroso paper Optimal Discrete Uniform Generation from Coin Flips, and Applications (2013) [2], who credits Donald E. Knuth and Andrew C. Yao, The complexity of nonuniform random number generation (1976), for solving the general case. The main advantage of this method is the that the unit of randomness is not the uniform random variable (uint32_t), but a random bit. It optimizes the internal buffer sampling by initially consuming a 32-bit random variable and then sampling byte per byte. Depending of the upper bound requested, it might lead to better CPU utilization. Checked on x86_64-linux-gnu, aarch64-linux, and powerpc64le-linux-gnu. Co-authored-by: Florian Weimer <fweimer@redhat.com> Reviewed-by: Yann Droneaud <ydroneaud@opteya.com> [1] https://datatracker.ietf.org/doc/html/rfc8439 [2] https://arxiv.org/pdf/1304.1916.pdf
2022-07-21 13:04:59 +00:00
stdlib: Simplify arc4random_uniform It uses the bitmask with rejection [1], which calculates a mask being the lowest power of two bounding the request upper bound, successively queries new random values, and rejects values outside the requested range. Performance-wise, there is no much gain in trying to conserve bits since arc4random is wrapper on getrandom syscall. It should be cheaper to just query a uint32_t value. The algorithm also avoids modulo and divide operations, which might be costly depending of the architecture. [1] https://www.pcg-random.org/posts/bounded-rands.html Reviewed-by: Yann Droneaud <ydroneaud@opteya.com>
2022-07-28 12:18:01 +00:00
/* mask is the smallest power of 2 minus 1 number larger than n. */
int z = __builtin_clz (n);
uint32_t mask = ~UINT32_C(0) >> z;
int bits = CHAR_BIT * sizeof (uint32_t) - z;
stdlib: Add arc4random, arc4random_buf, and arc4random_uniform (BZ #4417) The implementation is based on scalar Chacha20 with per-thread cache. It uses getrandom or /dev/urandom as fallback to get the initial entropy, and reseeds the internal state on every 16MB of consumed buffer. To improve performance and lower memory consumption the per-thread cache is allocated lazily on first arc4random functions call, and if the memory allocation fails getentropy or /dev/urandom is used as fallback. The cache is also cleared on thread exit iff it was initialized (so if arc4random is not called it is not touched). Although it is lock-free, arc4random is still not async-signal-safe (the per thread state is not updated atomically). The ChaCha20 implementation is based on RFC8439 [1], omitting the final XOR of the keystream with the plaintext because the plaintext is a stream of zeros. This strategy is similar to what OpenBSD arc4random does. The arc4random_uniform is based on previous work by Florian Weimer, where the algorithm is based on Jérémie Lumbroso paper Optimal Discrete Uniform Generation from Coin Flips, and Applications (2013) [2], who credits Donald E. Knuth and Andrew C. Yao, The complexity of nonuniform random number generation (1976), for solving the general case. The main advantage of this method is the that the unit of randomness is not the uniform random variable (uint32_t), but a random bit. It optimizes the internal buffer sampling by initially consuming a 32-bit random variable and then sampling byte per byte. Depending of the upper bound requested, it might lead to better CPU utilization. Checked on x86_64-linux-gnu, aarch64-linux, and powerpc64le-linux-gnu. Co-authored-by: Florian Weimer <fweimer@redhat.com> Reviewed-by: Yann Droneaud <ydroneaud@opteya.com> [1] https://datatracker.ietf.org/doc/html/rfc8439 [2] https://arxiv.org/pdf/1304.1916.pdf
2022-07-21 13:04:59 +00:00
stdlib: Simplify arc4random_uniform It uses the bitmask with rejection [1], which calculates a mask being the lowest power of two bounding the request upper bound, successively queries new random values, and rejects values outside the requested range. Performance-wise, there is no much gain in trying to conserve bits since arc4random is wrapper on getrandom syscall. It should be cheaper to just query a uint32_t value. The algorithm also avoids modulo and divide operations, which might be costly depending of the architecture. [1] https://www.pcg-random.org/posts/bounded-rands.html Reviewed-by: Yann Droneaud <ydroneaud@opteya.com>
2022-07-28 12:18:01 +00:00
while (1)
stdlib: Add arc4random, arc4random_buf, and arc4random_uniform (BZ #4417) The implementation is based on scalar Chacha20 with per-thread cache. It uses getrandom or /dev/urandom as fallback to get the initial entropy, and reseeds the internal state on every 16MB of consumed buffer. To improve performance and lower memory consumption the per-thread cache is allocated lazily on first arc4random functions call, and if the memory allocation fails getentropy or /dev/urandom is used as fallback. The cache is also cleared on thread exit iff it was initialized (so if arc4random is not called it is not touched). Although it is lock-free, arc4random is still not async-signal-safe (the per thread state is not updated atomically). The ChaCha20 implementation is based on RFC8439 [1], omitting the final XOR of the keystream with the plaintext because the plaintext is a stream of zeros. This strategy is similar to what OpenBSD arc4random does. The arc4random_uniform is based on previous work by Florian Weimer, where the algorithm is based on Jérémie Lumbroso paper Optimal Discrete Uniform Generation from Coin Flips, and Applications (2013) [2], who credits Donald E. Knuth and Andrew C. Yao, The complexity of nonuniform random number generation (1976), for solving the general case. The main advantage of this method is the that the unit of randomness is not the uniform random variable (uint32_t), but a random bit. It optimizes the internal buffer sampling by initially consuming a 32-bit random variable and then sampling byte per byte. Depending of the upper bound requested, it might lead to better CPU utilization. Checked on x86_64-linux-gnu, aarch64-linux, and powerpc64le-linux-gnu. Co-authored-by: Florian Weimer <fweimer@redhat.com> Reviewed-by: Yann Droneaud <ydroneaud@opteya.com> [1] https://datatracker.ietf.org/doc/html/rfc8439 [2] https://arxiv.org/pdf/1304.1916.pdf
2022-07-21 13:04:59 +00:00
{
stdlib: Simplify arc4random_uniform It uses the bitmask with rejection [1], which calculates a mask being the lowest power of two bounding the request upper bound, successively queries new random values, and rejects values outside the requested range. Performance-wise, there is no much gain in trying to conserve bits since arc4random is wrapper on getrandom syscall. It should be cheaper to just query a uint32_t value. The algorithm also avoids modulo and divide operations, which might be costly depending of the architecture. [1] https://www.pcg-random.org/posts/bounded-rands.html Reviewed-by: Yann Droneaud <ydroneaud@opteya.com>
2022-07-28 12:18:01 +00:00
uint32_t value = __arc4random ();
/* Return if the lower power of 2 minus 1 satisfy the condition. */
uint32_t r = value & mask;
if (r < n)
return r;
/* Otherwise check if remaining bits of entropy provides fits in the
bound. */
for (int bits_left = z; bits_left >= bits; bits_left -= bits)
{
value >>= bits;
r = value & mask;
if (r < n)
return r;
}
stdlib: Add arc4random, arc4random_buf, and arc4random_uniform (BZ #4417) The implementation is based on scalar Chacha20 with per-thread cache. It uses getrandom or /dev/urandom as fallback to get the initial entropy, and reseeds the internal state on every 16MB of consumed buffer. To improve performance and lower memory consumption the per-thread cache is allocated lazily on first arc4random functions call, and if the memory allocation fails getentropy or /dev/urandom is used as fallback. The cache is also cleared on thread exit iff it was initialized (so if arc4random is not called it is not touched). Although it is lock-free, arc4random is still not async-signal-safe (the per thread state is not updated atomically). The ChaCha20 implementation is based on RFC8439 [1], omitting the final XOR of the keystream with the plaintext because the plaintext is a stream of zeros. This strategy is similar to what OpenBSD arc4random does. The arc4random_uniform is based on previous work by Florian Weimer, where the algorithm is based on Jérémie Lumbroso paper Optimal Discrete Uniform Generation from Coin Flips, and Applications (2013) [2], who credits Donald E. Knuth and Andrew C. Yao, The complexity of nonuniform random number generation (1976), for solving the general case. The main advantage of this method is the that the unit of randomness is not the uniform random variable (uint32_t), but a random bit. It optimizes the internal buffer sampling by initially consuming a 32-bit random variable and then sampling byte per byte. Depending of the upper bound requested, it might lead to better CPU utilization. Checked on x86_64-linux-gnu, aarch64-linux, and powerpc64le-linux-gnu. Co-authored-by: Florian Weimer <fweimer@redhat.com> Reviewed-by: Yann Droneaud <ydroneaud@opteya.com> [1] https://datatracker.ietf.org/doc/html/rfc8439 [2] https://arxiv.org/pdf/1304.1916.pdf
2022-07-21 13:04:59 +00:00
}
}
libc_hidden_def (__arc4random_uniform)
weak_alias (__arc4random_uniform, arc4random_uniform)
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