| // Copyright 2017 The Rust Project Developers. See the COPYRIGHT |
| // file at the top-level directory of this distribution and at |
| // http://rust-lang.org/COPYRIGHT. |
| // |
| // Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or |
| // http://www.apache.org/licenses/LICENSE-2.0> or the MIT license |
| // <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your |
| // option. This file may not be copied, modified, or distributed |
| // except according to those terms. |
| // |
| // Based on jitterentropy-library, http://www.chronox.de/jent.html. |
| // Copyright Stephan Mueller <[email protected]>, 2014 - 2017. |
| // |
| // With permission from Stephan Mueller to relicense the Rust translation under |
| // the MIT license. |
| |
| //! Non-physical true random number generator based on timing jitter. |
| |
| use Rng; |
| |
| use core::{fmt, mem, ptr}; |
| #[cfg(feature="std")] |
| use std::sync::atomic::{AtomicUsize, ATOMIC_USIZE_INIT, Ordering}; |
| |
| const MEMORY_BLOCKS: usize = 64; |
| const MEMORY_BLOCKSIZE: usize = 32; |
| const MEMORY_SIZE: usize = MEMORY_BLOCKS * MEMORY_BLOCKSIZE; |
| |
| /// A true random number generator based on jitter in the CPU execution time, |
| /// and jitter in memory access time. |
| /// |
| /// This is a true random number generator, as opposed to pseudo-random |
| /// generators. Random numbers generated by `JitterRng` can be seen as fresh |
| /// entropy. A consequence is that is orders of magnitude slower than `OsRng` |
| /// and PRNGs (about 10^3 .. 10^6 slower). |
| /// |
| /// There are very few situations where using this RNG is appropriate. Only very |
| /// few applications require true entropy. A normal PRNG can be statistically |
| /// indistinguishable, and a cryptographic PRNG should also be as impossible to |
| /// predict. |
| /// |
| /// Use of `JitterRng` is recommended for initializing cryptographic PRNGs when |
| /// `OsRng` is not available. |
| /// |
| /// This implementation is based on |
| /// [Jitterentropy](http://www.chronox.de/jent.html) version 2.1.0. |
| // |
| // Note: the C implementation relies on being compiled without optimizations. |
| // This implementation goes through lengths to make the compiler not optimise |
| // out what is technically dead code, but that does influence timing jitter. |
| pub struct JitterRng { |
| data: u64, // Actual random number |
| // Number of rounds to run the entropy collector per 64 bits |
| rounds: u32, |
| // Timer and previous time stamp, used by `measure_jitter` |
| timer: fn() -> u64, |
| prev_time: u64, |
| // Deltas used for the stuck test |
| last_delta: i64, |
| last_delta2: i64, |
| // Memory for the Memory Access noise source |
| mem_prev_index: usize, |
| mem: [u8; MEMORY_SIZE], |
| // Make `next_u32` not waste 32 bits |
| data_remaining: Option<u32>, |
| } |
| |
| // Custom Debug implementation that does not expose the internal state |
| impl fmt::Debug for JitterRng { |
| fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result { |
| write!(f, "JitterRng {{}}") |
| } |
| } |
| |
| /// An error that can occur when `test_timer` fails. |
| #[derive(Debug, Clone, PartialEq, Eq)] |
| pub enum TimerError { |
| /// No timer available. |
| NoTimer, |
| /// Timer too coarse to use as an entropy source. |
| CoarseTimer, |
| /// Timer is not monotonically increasing. |
| NotMonotonic, |
| /// Variations of deltas of time too small. |
| TinyVariantions, |
| /// Too many stuck results (indicating no added entropy). |
| TooManyStuck, |
| #[doc(hidden)] |
| __Nonexhaustive, |
| } |
| |
| impl TimerError { |
| fn description(&self) -> &'static str { |
| match *self { |
| TimerError::NoTimer => "no timer available", |
| TimerError::CoarseTimer => "coarse timer", |
| TimerError::NotMonotonic => "timer not monotonic", |
| TimerError::TinyVariantions => "time delta variations too small", |
| TimerError::TooManyStuck => "too many stuck results", |
| TimerError::__Nonexhaustive => unreachable!(), |
| } |
| } |
| } |
| |
| impl fmt::Display for TimerError { |
| fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result { |
| write!(f, "{}", self.description()) |
| } |
| } |
| |
| #[cfg(feature="std")] |
| impl ::std::error::Error for TimerError { |
| fn description(&self) -> &str { |
| self.description() |
| } |
| } |
| |
| // Initialise to zero; must be positive |
| #[cfg(feature="std")] |
| static JITTER_ROUNDS: AtomicUsize = ATOMIC_USIZE_INIT; |
| |
| impl JitterRng { |
| /// Create a new `JitterRng`. |
| /// Makes use of `std::time` for a timer. |
| /// |
| /// During initialization CPU execution timing jitter is measured a few |
| /// hundred times. If this does not pass basic quality tests, an error is |
| /// returned. The test result is cached to make subsequent calls faster. |
| #[cfg(feature="std")] |
| pub fn new() -> Result<JitterRng, TimerError> { |
| let mut ec = JitterRng::new_with_timer(platform::get_nstime); |
| let mut rounds = JITTER_ROUNDS.load(Ordering::Relaxed) as u32; |
| if rounds == 0 { |
| // No result yet: run test. |
| // This allows the timer test to run multiple times; we don't care. |
| rounds = ec.test_timer()?; |
| JITTER_ROUNDS.store(rounds as usize, Ordering::Relaxed); |
| } |
| ec.set_rounds(rounds); |
| Ok(ec) |
| } |
| |
| /// Create a new `JitterRng`. |
| /// A custom timer can be supplied, making it possible to use `JitterRng` in |
| /// `no_std` environments. |
| /// |
| /// The timer must have nanosecond precision. |
| /// |
| /// This method is more low-level than `new()`. It is the responsibility of |
| /// the caller to run `test_timer` before using any numbers generated with |
| /// `JitterRng`, and optionally call `set_rounds()`. |
| pub fn new_with_timer(timer: fn() -> u64) -> JitterRng { |
| let mut ec = JitterRng { |
| data: 0, |
| rounds: 64, |
| timer: timer, |
| prev_time: 0, |
| last_delta: 0, |
| last_delta2: 0, |
| mem_prev_index: 0, |
| mem: [0; MEMORY_SIZE], |
| data_remaining: None, |
| }; |
| |
| // Fill `data`, `prev_time`, `last_delta` and `last_delta2` with |
| // non-zero values. |
| ec.prev_time = timer(); |
| ec.gen_entropy(); |
| |
| // Do a single read from `self.mem` to make sure the Memory Access noise |
| // source is not optimised out. |
| // Note: this read is important, it effects optimisations for the entire |
| // module! |
| black_box(ec.mem[0]); |
| |
| ec |
| } |
| |
| /// Configures how many rounds are used to generate each 64-bit value. |
| /// This must be greater than zero, and has a big impact on performance |
| /// and output quality. |
| /// |
| /// `new_with_timer` conservatively uses 64 rounds, but often less rounds |
| /// can be used. The `test_timer()` function returns the minimum number of |
| /// rounds required for full strength (platform dependent), so one may use |
| /// `rng.set_rounds(rng.test_timer()?);` or cache the value. |
| pub fn set_rounds(&mut self, rounds: u32) { |
| assert!(rounds > 0); |
| self.rounds = rounds; |
| } |
| |
| // Calculate a random loop count used for the next round of an entropy |
| // collection, based on bits from a fresh value from the timer. |
| // |
| // The timer is folded to produce a number that contains at most `n_bits` |
| // bits. |
| // |
| // Note: A constant should be added to the resulting random loop count to |
| // prevent loops that run 0 times. |
| #[inline(never)] |
| fn random_loop_cnt(&mut self, n_bits: u32) -> u32 { |
| let mut rounds = 0; |
| |
| let mut time = (self.timer)(); |
| // Mix with the current state of the random number balance the random |
| // loop counter a bit more. |
| time ^= self.data; |
| |
| // We fold the time value as much as possible to ensure that as many |
| // bits of the time stamp are included as possible. |
| let folds = (64 + n_bits - 1) / n_bits; |
| let mask = (1 << n_bits) - 1; |
| for _ in 0..folds { |
| rounds ^= time & mask; |
| time = time >> n_bits; |
| } |
| |
| rounds as u32 |
| } |
| |
| // CPU jitter noise source |
| // Noise source based on the CPU execution time jitter |
| // |
| // This function injects the individual bits of the time value into the |
| // entropy pool using an LFSR. |
| // |
| // The code is deliberately inefficient with respect to the bit shifting. |
| // This function not only acts as folding operation, but this function's |
| // execution is used to measure the CPU execution time jitter. Any change to |
| // the loop in this function implies that careful retesting must be done. |
| #[inline(never)] |
| fn lfsr_time(&mut self, time: u64, var_rounds: bool) { |
| fn lfsr(mut data: u64, time: u64) -> u64{ |
| for i in 1..65 { |
| let mut tmp = time << (64 - i); |
| tmp = tmp >> (64 - 1); |
| |
| // Fibonacci LSFR with polynomial of |
| // x^64 + x^61 + x^56 + x^31 + x^28 + x^23 + 1 which is |
| // primitive according to |
| // http://poincare.matf.bg.ac.rs/~ezivkovm/publications/primpol1.pdf |
| // (the shift values are the polynomial values minus one |
| // due to counting bits from 0 to 63). As the current |
| // position is always the LSB, the polynomial only needs |
| // to shift data in from the left without wrap. |
| data ^= tmp; |
| data ^= (data >> 63) & 1; |
| data ^= (data >> 60) & 1; |
| data ^= (data >> 55) & 1; |
| data ^= (data >> 30) & 1; |
| data ^= (data >> 27) & 1; |
| data ^= (data >> 22) & 1; |
| data = data.rotate_left(1); |
| } |
| data |
| } |
| |
| // Note: in the reference implementation only the last round effects |
| // `self.data`, all the other results are ignored. To make sure the |
| // other rounds are not optimised out, we first run all but the last |
| // round on a throw-away value instead of the real `self.data`. |
| let mut lfsr_loop_cnt = 0; |
| if var_rounds { lfsr_loop_cnt = self.random_loop_cnt(4) }; |
| |
| let mut throw_away: u64 = 0; |
| for _ in 0..lfsr_loop_cnt { |
| throw_away = lfsr(throw_away, time); |
| } |
| black_box(throw_away); |
| |
| self.data = lfsr(self.data, time); |
| } |
| |
| // Memory Access noise source |
| // This is a noise source based on variations in memory access times |
| // |
| // This function performs memory accesses which will add to the timing |
| // variations due to an unknown amount of CPU wait states that need to be |
| // added when accessing memory. The memory size should be larger than the L1 |
| // caches as outlined in the documentation and the associated testing. |
| // |
| // The L1 cache has a very high bandwidth, albeit its access rate is usually |
| // slower than accessing CPU registers. Therefore, L1 accesses only add |
| // minimal variations as the CPU has hardly to wait. Starting with L2, |
| // significant variations are added because L2 typically does not belong to |
| // the CPU any more and therefore a wider range of CPU wait states is |
| // necessary for accesses. L3 and real memory accesses have even a wider |
| // range of wait states. However, to reliably access either L3 or memory, |
| // the `self.mem` memory must be quite large which is usually not desirable. |
| #[inline(never)] |
| fn memaccess(&mut self, var_rounds: bool) { |
| let mut acc_loop_cnt = 128; |
| if var_rounds { acc_loop_cnt += self.random_loop_cnt(4) }; |
| |
| let mut index = self.mem_prev_index; |
| for _ in 0..acc_loop_cnt { |
| // Addition of memblocksize - 1 to index with wrap around logic to |
| // ensure that every memory location is hit evenly. |
| // The modulus also allows the compiler to remove the indexing |
| // bounds check. |
| index = (index + MEMORY_BLOCKSIZE - 1) % MEMORY_SIZE; |
| |
| // memory access: just add 1 to one byte |
| // memory access implies read from and write to memory location |
| let tmp = self.mem[index]; |
| self.mem[index] = tmp.wrapping_add(1); |
| } |
| self.mem_prev_index = index; |
| } |
| |
| |
| // Stuck test by checking the: |
| // - 1st derivation of the jitter measurement (time delta) |
| // - 2nd derivation of the jitter measurement (delta of time deltas) |
| // - 3rd derivation of the jitter measurement (delta of delta of time |
| // deltas) |
| // |
| // All values must always be non-zero. |
| // This test is a heuristic to see whether the last measurement holds |
| // entropy. |
| fn stuck(&mut self, current_delta: i64) -> bool { |
| let delta2 = self.last_delta - current_delta; |
| let delta3 = delta2 - self.last_delta2; |
| |
| self.last_delta = current_delta; |
| self.last_delta2 = delta2; |
| |
| current_delta == 0 || delta2 == 0 || delta3 == 0 |
| } |
| |
| // This is the heart of the entropy generation: calculate time deltas and |
| // use the CPU jitter in the time deltas. The jitter is injected into the |
| // entropy pool. |
| // |
| // Ensure that `self.prev_time` is primed before using the output of this |
| // function. This can be done by calling this function and not using its |
| // result. |
| fn measure_jitter(&mut self) -> Option<()> { |
| // Invoke one noise source before time measurement to add variations |
| self.memaccess(true); |
| |
| // Get time stamp and calculate time delta to previous |
| // invocation to measure the timing variations |
| let time = (self.timer)(); |
| // Note: wrapping_sub combined with a cast to `i64` generates a correct |
| // delta, even in the unlikely case this is a timer that is not strictly |
| // monotonic. |
| let current_delta = time.wrapping_sub(self.prev_time) as i64; |
| self.prev_time = time; |
| |
| // Call the next noise source which also injects the data |
| self.lfsr_time(current_delta as u64, true); |
| |
| // Check whether we have a stuck measurement (i.e. does the last |
| // measurement holds entropy?). |
| if self.stuck(current_delta) { return None }; |
| |
| // Rotate the data buffer by a prime number (any odd number would |
| // do) to ensure that every bit position of the input time stamp |
| // has an even chance of being merged with a bit position in the |
| // entropy pool. We do not use one here as the adjacent bits in |
| // successive time deltas may have some form of dependency. The |
| // chosen value of 7 implies that the low 7 bits of the next |
| // time delta value is concatenated with the current time delta. |
| self.data = self.data.rotate_left(7); |
| |
| Some(()) |
| } |
| |
| // Shuffle the pool a bit by mixing some value with a bijective function |
| // (XOR) into the pool. |
| // |
| // The function generates a mixer value that depends on the bits set and |
| // the location of the set bits in the random number generated by the |
| // entropy source. Therefore, based on the generated random number, this |
| // mixer value can have 2^64 different values. That mixer value is |
| // initialized with the first two SHA-1 constants. After obtaining the |
| // mixer value, it is XORed into the random number. |
| // |
| // The mixer value is not assumed to contain any entropy. But due to the |
| // XOR operation, it can also not destroy any entropy present in the |
| // entropy pool. |
| #[inline(never)] |
| fn stir_pool(&mut self) { |
| // This constant is derived from the first two 32 bit initialization |
| // vectors of SHA-1 as defined in FIPS 180-4 section 5.3.1 |
| // The order does not really matter as we do not rely on the specific |
| // numbers. We just pick the SHA-1 constants as they have a good mix of |
| // bit set and unset. |
| const CONSTANT: u64 = 0x67452301efcdab89; |
| |
| // The start value of the mixer variable is derived from the third |
| // and fourth 32 bit initialization vector of SHA-1 as defined in |
| // FIPS 180-4 section 5.3.1 |
| let mut mixer = 0x98badcfe10325476; |
| |
| // This is a constant time function to prevent leaking timing |
| // information about the random number. |
| // The normal code is: |
| // ``` |
| // for i in 0..64 { |
| // if ((self.data >> i) & 1) == 1 { mixer ^= CONSTANT; } |
| // } |
| // ``` |
| // This is a bit fragile, as LLVM really wants to use branches here, and |
| // we rely on it to not recognise the opportunity. |
| for i in 0..64 { |
| let apply = (self.data >> i) & 1; |
| let mask = !apply.wrapping_sub(1); |
| mixer ^= CONSTANT & mask; |
| mixer = mixer.rotate_left(1); |
| } |
| |
| self.data ^= mixer; |
| } |
| |
| fn gen_entropy(&mut self) -> u64 { |
| // Prime `self.prev_time`, and run the noice sources to make sure the |
| // first loop round collects the expected entropy. |
| let _ = self.measure_jitter(); |
| |
| for _ in 0..self.rounds { |
| // If a stuck measurement is received, repeat measurement |
| // Note: we do not guard against an infinite loop, that would mean |
| // the timer suddenly became broken. |
| while self.measure_jitter().is_none() {} |
| } |
| |
| self.stir_pool(); |
| self.data |
| } |
| |
| /// Basic quality tests on the timer, by measuring CPU timing jitter a few |
| /// hundred times. |
| /// |
| /// If succesful, this will return the estimated number of rounds necessary |
| /// to collect 64 bits of entropy. Otherwise a `TimerError` with the cause |
| /// of the failure will be returned. |
| pub fn test_timer(&mut self) -> Result<u32, TimerError> { |
| // We could add a check for system capabilities such as `clock_getres` |
| // or check for `CONFIG_X86_TSC`, but it does not make much sense as the |
| // following sanity checks verify that we have a high-resolution timer. |
| |
| #[cfg(all(target_arch = "wasm32", not(target_os = "emscripten")))] |
| return Err(TimerError::NoTimer); |
| |
| let mut delta_sum = 0; |
| let mut old_delta = 0; |
| |
| let mut time_backwards = 0; |
| let mut count_mod = 0; |
| let mut count_stuck = 0; |
| |
| // TESTLOOPCOUNT needs some loops to identify edge systems. |
| // 100 is definitely too little. |
| const TESTLOOPCOUNT: u64 = 300; |
| const CLEARCACHE: u64 = 100; |
| |
| for i in 0..(CLEARCACHE + TESTLOOPCOUNT) { |
| // Measure time delta of core entropy collection logic |
| let time = (self.timer)(); |
| self.memaccess(true); |
| self.lfsr_time(time, true); |
| let time2 = (self.timer)(); |
| |
| // Test whether timer works |
| if time == 0 || time2 == 0 { |
| return Err(TimerError::NoTimer); |
| } |
| let delta = time2.wrapping_sub(time) as i64; |
| |
| // Test whether timer is fine grained enough to provide delta even |
| // when called shortly after each other -- this implies that we also |
| // have a high resolution timer |
| if delta == 0 { |
| return Err(TimerError::CoarseTimer); |
| } |
| |
| // Up to here we did not modify any variable that will be |
| // evaluated later, but we already performed some work. Thus we |
| // already have had an impact on the caches, branch prediction, |
| // etc. with the goal to clear it to get the worst case |
| // measurements. |
| if i < CLEARCACHE { continue; } |
| |
| if self.stuck(delta) { count_stuck += 1; } |
| |
| // Test whether we have an increasing timer. |
| if !(time2 > time) { time_backwards += 1; } |
| |
| // Count the number of times the counter increases in steps of 100ns |
| // or greater. |
| if (delta % 100) == 0 { count_mod += 1; } |
| |
| // Ensure that we have a varying delta timer which is necessary for |
| // the calculation of entropy -- perform this check only after the |
| // first loop is executed as we need to prime the old_delta value |
| delta_sum += (delta - old_delta).abs() as u64; |
| old_delta = delta; |
| } |
| |
| // We allow the time to run backwards for up to three times. |
| // This can happen if the clock is being adjusted by NTP operations. |
| // If such an operation just happens to interfere with our test, it |
| // should not fail. The value of 3 should cover the NTP case being |
| // performed during our test run. |
| if time_backwards > 3 { |
| return Err(TimerError::NotMonotonic); |
| } |
| |
| // Test that the available amount of entropy per round does not get to |
| // low. We expect 1 bit of entropy per round as a reasonable minimum |
| // (although less is possible, it means the collector loop has to run |
| // much more often). |
| // `assert!(delta_average >= log2(1))` |
| // `assert!(delta_sum / TESTLOOPCOUNT >= 1)` |
| // `assert!(delta_sum >= TESTLOOPCOUNT)` |
| if delta_sum < TESTLOOPCOUNT { |
| return Err(TimerError::TinyVariantions); |
| } |
| |
| // Ensure that we have variations in the time stamp below 100 for at |
| // least 10% of all checks -- on some platforms, the counter increments |
| // in multiples of 100, but not always |
| if count_mod > (TESTLOOPCOUNT * 9 / 10) { |
| return Err(TimerError::CoarseTimer); |
| } |
| |
| // If we have more than 90% stuck results, then this Jitter RNG is |
| // likely to not work well. |
| if count_stuck > (TESTLOOPCOUNT * 9 / 10) { |
| return Err(TimerError::TooManyStuck); |
| } |
| |
| // Estimate the number of `measure_jitter` rounds necessary for 64 bits |
| // of entropy. |
| // |
| // We don't try very hard to come up with a good estimate of the |
| // available bits of entropy per round here for two reasons: |
| // 1. Simple estimates of the available bits (like Shannon entropy) are |
| // too optimistic. |
| // 2) Unless we want to waste a lot of time during intialization, there |
| // only a small number of samples are available. |
| // |
| // Therefore we use a very simple and conservative estimate: |
| // `let bits_of_entropy = log2(delta_average) / 2`. |
| // |
| // The number of rounds `measure_jitter` should run to collect 64 bits |
| // of entropy is `64 / bits_of_entropy`. |
| // |
| // To have smaller rounding errors, intermediate values are multiplied |
| // by `FACTOR`. To compensate for `log2` and division rounding down, |
| // add 1. |
| let delta_average = delta_sum / TESTLOOPCOUNT; |
| // println!("delta_average: {}", delta_average); |
| |
| const FACTOR: u32 = 3; |
| fn log2(x: u64) -> u32 { 64 - x.leading_zeros() } |
| |
| // pow(δ, FACTOR) must be representable; if you have overflow reduce FACTOR |
| Ok(64 * 2 * FACTOR / (log2(delta_average.pow(FACTOR)) + 1)) |
| } |
| |
| /// Statistical test: return the timer delta of one normal run of the |
| /// `JitterEntropy` entropy collector. |
| /// |
| /// Setting `var_rounds` to `true` will execute the memory access and the |
| /// CPU jitter noice sources a variable amount of times (just like a real |
| /// `JitterEntropy` round). |
| /// |
| /// Setting `var_rounds` to `false` will execute the noice sources the |
| /// minimal number of times. This can be used to measure the minimum amount |
| /// of entropy one round of entropy collector can collect in the worst case. |
| /// |
| /// # Example |
| /// |
| /// Use `timer_stats` to run the [NIST SP 800-90B Entropy Estimation Suite] |
| /// (https://github.com/usnistgov/SP800-90B_EntropyAssessment). |
| /// |
| /// This is the recommended way to test the quality of `JitterRng`. It |
| /// should be run before using the RNG on untested hardware, after changes |
| /// that could effect how the code is optimised, and after major compiler |
| /// compiler changes, like a new LLVM version. |
| /// |
| /// First generate two files `jitter_rng_var.bin` and `jitter_rng_var.min`. |
| /// |
| /// Execute `python noniid_main.py -v jitter_rng_var.bin 8`, and validate it |
| /// with `restart.py -v jitter_rng_var.bin 8 <min-entropy>`. |
| /// This number is the expected amount of entropy that is at least available |
| /// for each round of the entropy collector. This number should be greater |
| /// than the amount estimated with `64 / test_timer()`. |
| /// |
| /// Execute `python noniid_main.py -v -u 4 jitter_rng_var.bin 4`, and |
| /// validate it with `restart.py -v -u 4 jitter_rng_var.bin 4 <min-entropy>`. |
| /// This number is the expected amount of entropy that is available in the |
| /// last 4 bits of the timer delta after running noice sources. Note that |
| /// a value of 3.70 is the minimum estimated entropy for true randomness. |
| /// |
| /// Execute `python noniid_main.py -v -u 4 jitter_rng_var.bin 4`, and |
| /// validate it with `restart.py -v -u 4 jitter_rng_var.bin 4 <min-entropy>`. |
| /// This number is the expected amount of entropy that is available to the |
| /// entropy collecter if both noice sources only run their minimal number of |
| /// times. This measures the absolute worst-case, and gives a lower bound |
| /// for the available entropy. |
| /// |
| /// ```rust,no_run |
| /// use rand::JitterRng; |
| /// |
| /// # use std::error::Error; |
| /// # use std::fs::File; |
| /// # use std::io::Write; |
| /// # |
| /// # fn try_main() -> Result<(), Box<Error>> { |
| /// fn get_nstime() -> u64 { |
| /// use std::time::{SystemTime, UNIX_EPOCH}; |
| /// |
| /// let dur = SystemTime::now().duration_since(UNIX_EPOCH).unwrap(); |
| /// // The correct way to calculate the current time is |
| /// // `dur.as_secs() * 1_000_000_000 + dur.subsec_nanos() as u64` |
| /// // But this is faster, and the difference in terms of entropy is |
| /// // negligible (log2(10^9) == 29.9). |
| /// dur.as_secs() << 30 | dur.subsec_nanos() as u64 |
| /// } |
| /// |
| /// // Do not initialize with `JitterRng::new`, but with `new_with_timer`. |
| /// // 'new' always runst `test_timer`, and can therefore fail to |
| /// // initialize. We want to be able to get the statistics even when the |
| /// // timer test fails. |
| /// let mut rng = JitterRng::new_with_timer(get_nstime); |
| /// |
| /// // 1_000_000 results are required for the NIST SP 800-90B Entropy |
| /// // Estimation Suite |
| /// // FIXME: this number is smaller here, otherwise the Doc-test is too slow |
| /// const ROUNDS: usize = 10_000; |
| /// let mut deltas_variable: Vec<u8> = Vec::with_capacity(ROUNDS); |
| /// let mut deltas_minimal: Vec<u8> = Vec::with_capacity(ROUNDS); |
| /// |
| /// for _ in 0..ROUNDS { |
| /// deltas_variable.push(rng.timer_stats(true) as u8); |
| /// deltas_minimal.push(rng.timer_stats(false) as u8); |
| /// } |
| /// |
| /// // Write out after the statistics collection loop, to not disturb the |
| /// // test results. |
| /// File::create("jitter_rng_var.bin")?.write(&deltas_variable)?; |
| /// File::create("jitter_rng_min.bin")?.write(&deltas_minimal)?; |
| /// # |
| /// # Ok(()) |
| /// # } |
| /// # |
| /// # fn main() { |
| /// # try_main().unwrap(); |
| /// # } |
| /// ``` |
| #[cfg(feature="std")] |
| pub fn timer_stats(&mut self, var_rounds: bool) -> i64 { |
| let time = platform::get_nstime(); |
| self.memaccess(var_rounds); |
| self.lfsr_time(time, var_rounds); |
| let time2 = platform::get_nstime(); |
| time2.wrapping_sub(time) as i64 |
| } |
| } |
| |
| #[cfg(feature="std")] |
| mod platform { |
| #[cfg(not(any(target_os = "macos", target_os = "ios", target_os = "windows", all(target_arch = "wasm32", not(target_os = "emscripten")))))] |
| pub fn get_nstime() -> u64 { |
| use std::time::{SystemTime, UNIX_EPOCH}; |
| |
| let dur = SystemTime::now().duration_since(UNIX_EPOCH).unwrap(); |
| // The correct way to calculate the current time is |
| // `dur.as_secs() * 1_000_000_000 + dur.subsec_nanos() as u64` |
| // But this is faster, and the difference in terms of entropy is negligible |
| // (log2(10^9) == 29.9). |
| dur.as_secs() << 30 | dur.subsec_nanos() as u64 |
| } |
| |
| #[cfg(any(target_os = "macos", target_os = "ios"))] |
| pub fn get_nstime() -> u64 { |
| extern crate libc; |
| // On Mac OS and iOS std::time::SystemTime only has 1000ns resolution. |
| // We use `mach_absolute_time` instead. This provides a CPU dependent unit, |
| // to get real nanoseconds the result should by multiplied by numer/denom |
| // from `mach_timebase_info`. |
| // But we are not interested in the exact nanoseconds, just entropy. So we |
| // use the raw result. |
| unsafe { libc::mach_absolute_time() } |
| } |
| |
| #[cfg(target_os = "windows")] |
| pub fn get_nstime() -> u64 { |
| extern crate winapi; |
| unsafe { |
| let mut t = super::mem::zeroed(); |
| winapi::um::profileapi::QueryPerformanceCounter(&mut t); |
| *t.QuadPart() as u64 |
| } |
| } |
| |
| #[cfg(all(target_arch = "wasm32", not(target_os = "emscripten")))] |
| pub fn get_nstime() -> u64 { |
| unreachable!() |
| } |
| } |
| |
| // A function that is opaque to the optimizer to assist in avoiding dead-code |
| // elimination. Taken from `bencher`. |
| fn black_box<T>(dummy: T) -> T { |
| unsafe { |
| let ret = ptr::read_volatile(&dummy); |
| mem::forget(dummy); |
| ret |
| } |
| } |
| |
| impl Rng for JitterRng { |
| fn next_u32(&mut self) -> u32 { |
| // We want to use both parts of the generated entropy |
| if let Some(high) = self.data_remaining.take() { |
| high |
| } else { |
| let data = self.next_u64(); |
| self.data_remaining = Some((data >> 32) as u32); |
| data as u32 |
| } |
| } |
| |
| fn next_u64(&mut self) -> u64 { |
| self.gen_entropy() |
| } |
| |
| fn fill_bytes(&mut self, dest: &mut [u8]) { |
| let mut left = dest; |
| while left.len() >= 8 { |
| let (l, r) = {left}.split_at_mut(8); |
| left = r; |
| let chunk: [u8; 8] = unsafe { |
| mem::transmute(self.next_u64().to_le()) |
| }; |
| l.copy_from_slice(&chunk); |
| } |
| let n = left.len(); |
| if n > 0 { |
| let chunk: [u8; 8] = unsafe { |
| mem::transmute(self.next_u64().to_le()) |
| }; |
| left.copy_from_slice(&chunk[..n]); |
| } |
| } |
| } |
| |
| // There are no tests included because (1) this is an "external" RNG, so output |
| // is not reproducible and (2) `test_timer` *will* fail on some platforms. |
