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/* | |
Copyright (c) 2024 Orson Peters <orsonpeters@gmail.com> | |
This software is provided 'as-is', without any express or implied warranty. In no event will the | |
authors be held liable for any damages arising from the use of this software. | |
Permission is granted to anyone to use this software for any purpose, including commercial | |
applications, and to alter it and redistribute it freely, subject to the following restrictions: | |
1. The origin of this software must not be misrepresented; you must not claim that you wrote the | |
original software. If you use this software in a product, an acknowledgment in the product | |
documentation would be appreciated but is not required. | |
2. Altered source versions must be plainly marked as such, and must not be misrepresented as | |
being the original software. | |
3. This notice may not be removed or altered from any source distribution. | |
*/ | |
#include <cstdlib> | |
#include <iosfwd> | |
#include <cstdint> | |
#include <limits> | |
template<size_t R> | |
class ChaCha { | |
public: | |
typedef uint32_t result_type; | |
explicit ChaCha(uint64_t seedval, uint64_t stream = 0); | |
template<class Sseq> explicit ChaCha(Sseq& seq); | |
void seed(uint64_t seedval, uint64_t stream = 0); | |
template<class Sseq> void seed(Sseq& seq); | |
uint32_t operator()(); | |
void discard(unsigned long long n); | |
template<size_t R_> friend bool operator==(const ChaCha<R_>& lhs, const ChaCha<R_>& rhs); | |
template<size_t R_> friend bool operator!=(const ChaCha<R_>& lhs, const ChaCha<R_>& rhs); | |
template<typename CharT, typename Traits> | |
friend std::basic_ostream<CharT, Traits>& operator<<(std::basic_ostream<CharT, Traits>& os, const ChaCha<R>& rng); | |
template<typename CharT, typename Traits> | |
friend std::basic_istream<CharT, Traits>& operator>>(std::basic_istream<CharT, Traits>& is, ChaCha<R>& rng); | |
static constexpr uint32_t min() { return std::numeric_limits<uint32_t>::min(); } | |
static constexpr uint32_t max() { return std::numeric_limits<uint32_t>::max(); } | |
private: | |
void generate_block(); | |
void chacha_core(); | |
alignas(16) uint32_t block[16]; | |
uint64_t block_idx; | |
uint32_t keysetup[8]; | |
uint64_t ctr; | |
}; | |
template<size_t R> | |
inline ChaCha<R>::ChaCha(uint64_t seedval, uint64_t stream) { | |
seed(seedval, stream); | |
} | |
template<size_t R> | |
template<class Sseq> | |
inline ChaCha<R>::ChaCha(Sseq& seq) { | |
seed(seq); | |
} | |
template<size_t R> | |
inline void ChaCha<R>::seed(uint64_t seedval, uint64_t stream) { | |
ctr = 0; | |
block_idx = uint64_t(-1); // Block is assumed to be uninitialized. | |
keysetup[0] = seedval & 0xffffffffu; | |
keysetup[1] = seedval >> 32; | |
keysetup[2] = keysetup[3] = 0xdeadbeef; // Could use 128-bit seed. | |
keysetup[4] = stream & 0xffffffffu; | |
keysetup[5] = stream >> 32; | |
keysetup[6] = keysetup[7] = 0xdeadbeef; // Could use 128-bit stream. | |
} | |
template<size_t R> | |
template<class Sseq> | |
inline void ChaCha<R>::seed(Sseq& seq) { | |
ctr = 0; | |
block_idx = uint64_t(-1); // Block is assumed to be uninitialized. | |
seq.generate(keysetup, keysetup + 8); | |
} | |
template<size_t R> | |
inline uint32_t ChaCha<R>::operator()() { | |
uint64_t next_block_idx = ctr / 16; | |
uint64_t idx_in_block = ctr % 16; | |
if (next_block_idx != block_idx) { | |
block_idx = next_block_idx; | |
generate_block(); | |
} | |
++ctr; | |
return block[idx_in_block]; | |
} | |
template<size_t R> | |
inline void ChaCha<R>::discard(unsigned long long n) { | |
ctr += n; | |
} | |
template<size_t R> | |
inline void ChaCha<R>::generate_block() { | |
uint32_t constants[4] = {0x61707865, 0x3320646e, 0x79622d32, 0x6b206574}; | |
uint32_t input[16]; | |
for (int i = 0; i < 4; ++i) input[i] = constants[i]; | |
for (int i = 0; i < 8; ++i) input[4 + i] = keysetup[i]; | |
input[12] = block_idx & 0xffffffffu; | |
input[13] = block_idx >> 32; | |
input[14] = input[15] = 0xdeadbeef; // Could use 128-bit counter. | |
for (int i = 0; i < 16; ++i) block[i] = input[i]; | |
chacha_core(); | |
for (int i = 0; i < 16; ++i) block[i] += input[i]; | |
} | |
#ifdef __SSE2__ | |
#include "emmintrin.h" | |
// Get an efficient _mm_roti_epi32 based on enabled features. | |
#if !defined(__XOP__) | |
#if defined(__SSSE3__) | |
#include <tmmintrin.h> | |
#define _mm_roti_epi32(r, c) ( \ | |
((c) == 8) ? \ | |
_mm_shuffle_epi8((r), _mm_set_epi8(14, 13, 12, 15, \ | |
10, 9, 8, 11, \ | |
6, 5, 4, 7, \ | |
2, 1, 0, 3)) \ | |
: ((c) == 16) ? \ | |
_mm_shuffle_epi8((r), _mm_set_epi8(13, 12, 15, 14, \ | |
9, 8, 11, 10, \ | |
5, 4, 7, 6, \ | |
1, 0, 3, 2)) \ | |
: ((c) == 24) ? \ | |
_mm_shuffle_epi8((r), _mm_set_epi8(12, 15, 14, 13, \ | |
8, 11, 10, 9, \ | |
4, 7, 6, 5, \ | |
0, 3, 2, 1)) \ | |
: \ | |
_mm_xor_si128(_mm_slli_epi32((r), (c)), \ | |
_mm_srli_epi32((r), 32-(c))) \ | |
) | |
#else | |
#define _mm_roti_epi32(r, c) _mm_xor_si128(_mm_slli_epi32((r), (c)), \ | |
_mm_srli_epi32((r), 32-(c))) | |
#endif | |
#else | |
#include <xopintrin.h> | |
#endif | |
template<size_t R> | |
inline void ChaCha<R>::chacha_core() { | |
// ROTVn rotates the elements in the given vector n places to the left. | |
#define CHACHA_ROTV1(x) _mm_shuffle_epi32((__m128i) x, 0x39) | |
#define CHACHA_ROTV2(x) _mm_shuffle_epi32((__m128i) x, 0x4e) | |
#define CHACHA_ROTV3(x) _mm_shuffle_epi32((__m128i) x, 0x93) | |
__m128i a = _mm_load_si128((__m128i*) (block)); | |
__m128i b = _mm_load_si128((__m128i*) (block + 4)); | |
__m128i c = _mm_load_si128((__m128i*) (block + 8)); | |
__m128i d = _mm_load_si128((__m128i*) (block + 12)); | |
for (int i = 0; i < R; i += 2) { | |
a = _mm_add_epi32(a, b); | |
d = _mm_xor_si128(d, a); | |
d = _mm_roti_epi32(d, 16); | |
c = _mm_add_epi32(c, d); | |
b = _mm_xor_si128(b, c); | |
b = _mm_roti_epi32(b, 12); | |
a = _mm_add_epi32(a, b); | |
d = _mm_xor_si128(d, a); | |
d = _mm_roti_epi32(d, 8); | |
c = _mm_add_epi32(c, d); | |
b = _mm_xor_si128(b, c); | |
b = _mm_roti_epi32(b, 7); | |
b = CHACHA_ROTV1(b); | |
c = CHACHA_ROTV2(c); | |
d = CHACHA_ROTV3(d); | |
a = _mm_add_epi32(a, b); | |
d = _mm_xor_si128(d, a); | |
d = _mm_roti_epi32(d, 16); | |
c = _mm_add_epi32(c, d); | |
b = _mm_xor_si128(b, c); | |
b = _mm_roti_epi32(b, 12); | |
a = _mm_add_epi32(a, b); | |
d = _mm_xor_si128(d, a); | |
d = _mm_roti_epi32(d, 8); | |
c = _mm_add_epi32(c, d); | |
b = _mm_xor_si128(b, c); | |
b = _mm_roti_epi32(b, 7); | |
b = CHACHA_ROTV3(b); | |
c = CHACHA_ROTV2(c); | |
d = CHACHA_ROTV1(d); | |
} | |
_mm_store_si128((__m128i*) (block), a); | |
_mm_store_si128((__m128i*) (block + 4), b); | |
_mm_store_si128((__m128i*) (block + 8), c); | |
_mm_store_si128((__m128i*) (block + 12), d); | |
#undef CHACHA_ROTV3 | |
#undef CHACHA_ROTV2 | |
#undef CHACHA_ROTV1 | |
} | |
#else | |
template<size_t R> | |
inline void ChaCha<R>::chacha_core() { | |
#define CHACHA_ROTL32(x, n) (((x) << (n)) | ((x) >> (32 - (n)))) | |
#define CHACHA_QUARTERROUND(x, a, b, c, d) \ | |
x[a] = x[a] + x[b]; x[d] ^= x[a]; x[d] = CHACHA_ROTL32(x[d], 16); \ | |
x[c] = x[c] + x[d]; x[b] ^= x[c]; x[b] = CHACHA_ROTL32(x[b], 12); \ | |
x[a] = x[a] + x[b]; x[d] ^= x[a]; x[d] = CHACHA_ROTL32(x[d], 8); \ | |
x[c] = x[c] + x[d]; x[b] ^= x[c]; x[b] = CHACHA_ROTL32(x[b], 7) | |
for (int i = 0; i < R; i += 2) { | |
CHACHA_QUARTERROUND(block, 0, 4, 8, 12); | |
CHACHA_QUARTERROUND(block, 1, 5, 9, 13); | |
CHACHA_QUARTERROUND(block, 2, 6, 10, 14); | |
CHACHA_QUARTERROUND(block, 3, 7, 11, 15); | |
CHACHA_QUARTERROUND(block, 0, 5, 10, 15); | |
CHACHA_QUARTERROUND(block, 1, 6, 11, 12); | |
CHACHA_QUARTERROUND(block, 2, 7, 8, 13); | |
CHACHA_QUARTERROUND(block, 3, 4, 9, 14); | |
} | |
#undef CHACHA_QUARTERROUND | |
#undef CHACHA_ROTL32 | |
} | |
#endif | |
// Implement <random> interface. | |
template<size_t R> | |
inline bool operator==(const ChaCha<R>& lhs, const ChaCha<R>& rhs) { | |
for (int i = 0; i < 8; ++i) { | |
if (lhs.keysetup[i] != rhs.keysetup[i]) return false; | |
} | |
return lhs.ctr == rhs.ctr; | |
} | |
template<size_t R> | |
inline bool operator!=(const ChaCha<R>& lhs, const ChaCha<R>& rhs) { return !(lhs == rhs); } | |
template<size_t R, typename CharT, typename Traits> | |
inline std::basic_ostream<CharT, Traits>& operator<<(std::basic_ostream<CharT, Traits>& os, const ChaCha<R>& rng) { | |
typedef typename std::basic_ostream<CharT, Traits>::ios_base ios_base; | |
// Save old state. | |
auto flags = os.flags(); | |
auto fill = os.fill(); | |
// Set flags and fill to space. | |
auto space = os.widen(' '); | |
os.flags(ios_base::dec | ios_base::fixed | ios_base::left); | |
os.fill(space); | |
// Serialize. | |
for (int i = 0; i < 8; ++i) os << rng.keysetup[i] << space; | |
os << rng.ctr; | |
// Sestore old state. | |
os.flags(flags); | |
os.fill(fill); | |
return os; | |
} | |
template<size_t R, typename CharT, typename Traits> | |
inline std::basic_istream<CharT, Traits>& operator>>(std::basic_istream<CharT, Traits>& is, ChaCha<R>& rng) { | |
typedef typename std::basic_istream<CharT, Traits> ::ios_base ios_base; | |
// Save old flags and set ours. | |
auto flags = is.flags(); | |
is.flags(ios_base::dec); | |
// Deserialize. | |
for (int i = 0; i < 8; ++i) is >> rng.keysetup[i]; | |
is >> rng.ctr; | |
rng.block_idx = uint64_t(-1); // Block is assumed to be uninitialized. | |
// Restore old flags. | |
is.flags(flags); | |
return is; | |
} |
Oof that's nasty, good catch, will fix in a bit.
@gg-yb Should be fixed now.
Does this bug referenced by @gg-yb affect the C implementation of the python randomgen
package here: https://github.com/bashtage/randomgen/blob/main/randomgen/src/chacha/chacha.h ? It uses a 128 bit counter as a 2 element array of 64bit integers. It's not quite clear to me from looking at the code.
@zoj613 They use subtly different logic than my old version. They also always initialize the block on first seeding.
That said, it is quite an error-prone method (which I am completely to blame for). I believe they are vulnerable to a different failure mode:
- Seed the RNG.
- Advance 15.
- Call the RNG.
- Advance 1.
- Call the RNG (this call now has the wrong RNG block).
That is for the underlying RNG. You can see this issue by advancing 14 / 2 as well, which is necessary when showing the issue from Python as the random_raw
advances in steps of 2:
>>> c = randomgen.ChaCha(seed = 42)
>>> c.random_raw()
9683234991490822391
>>> c.random_raw()
8718982787486621969
>>> c = randomgen.ChaCha(seed = 42)
>>> c.advance(2).random_raw()
8718982787486621969
So to reproduce in Python, you can do it as follows:
>>> c = randomgen.ChaCha(seed = 42)
>>> first16 = c.random_raw(16)
>>> c = randomgen.ChaCha(seed = 42)
>>> c.advance(14).random_raw();
>>> c.advance(2);
>>> bugged = c.random_raw(7)
>>> bugged == first16[1:8]
array([ True, True, True, True, True, True, True])
Thanks for the explanation. I think I understand it a bit better now, though not sure what would be the best approach to avoid this in python. More importantly, I'd like to know since my Ocaml port of the code is based on the C code and reproduces the python bug. @bashtage Maybe you have a better idea of how this could be solved as the author of the C99 port?
Thanks for including me. I have removed advance
and related methods from chacha. I think I wasn't careful enough in thinking about the need for a block cipher based CBRNG to use these methods.
There seems to be a bug with discard (under the assumption that it should work as if operator() had been called n times):
Consider a fresh RNG with ctr = 0. block is uninitialized.
Now, discard(1).
ctr = 1, but the condition in discard does not hold and block is still uninitialized.
Now call operator(). The condition inside does not hold, and block is still uninitialized, and uninitialized memory is returned.
From our internal bugtracker:
Best Regards
gg-yb