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Diffstat (limited to 'rand/rand_core/src/lib.rs')
| -rw-r--r-- | rand/rand_core/src/lib.rs | 492 |
1 files changed, 0 insertions, 492 deletions
diff --git a/rand/rand_core/src/lib.rs b/rand/rand_core/src/lib.rs deleted file mode 100644 index d8e0189..0000000 --- a/rand/rand_core/src/lib.rs +++ /dev/null @@ -1,492 +0,0 @@ -// Copyright 2018 Developers of the Rand project. -// Copyright 2017-2018 The Rust Project Developers. -// -// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or -// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license -// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your -// option. This file may not be copied, modified, or distributed -// except according to those terms. - -//! Random number generation traits -//! -//! This crate is mainly of interest to crates publishing implementations of -//! [`RngCore`]. Other users are encouraged to use the [`rand`] crate instead -//! which re-exports the main traits and error types. -//! -//! [`RngCore`] is the core trait implemented by algorithmic pseudo-random number -//! generators and external random-number sources. -//! -//! [`SeedableRng`] is an extension trait for construction from fixed seeds and -//! other random number generators. -//! -//! [`Error`] is provided for error-handling. It is safe to use in `no_std` -//! environments. -//! -//! The [`impls`] and [`le`] sub-modules include a few small functions to assist -//! implementation of [`RngCore`]. -//! -//! [`rand`]: https://docs.rs/rand - -#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png", - html_favicon_url = "https://www.rust-lang.org/favicon.ico", - html_root_url = "https://rust-random.github.io/rand/")] - -#![deny(missing_docs)] -#![deny(missing_debug_implementations)] -#![doc(test(attr(allow(unused_variables), deny(warnings))))] - -#![allow(clippy::unreadable_literal)] - -#![cfg_attr(not(feature="std"), no_std)] - - -use core::default::Default; -use core::convert::AsMut; -use core::ptr::copy_nonoverlapping; - -#[cfg(all(feature="alloc", not(feature="std")))] extern crate alloc; -#[cfg(all(feature="alloc", not(feature="std")))] use alloc::boxed::Box; - -pub use error::Error; -#[cfg(feature="getrandom")] pub use os::OsRng; - - -mod error; -pub mod block; -pub mod impls; -pub mod le; -#[cfg(feature="getrandom")] mod os; - - -/// The core of a random number generator. -/// -/// This trait encapsulates the low-level functionality common to all -/// generators, and is the "back end", to be implemented by generators. -/// End users should normally use the `Rng` trait from the [`rand`] crate, -/// which is automatically implemented for every type implementing `RngCore`. -/// -/// Three different methods for generating random data are provided since the -/// optimal implementation of each is dependent on the type of generator. There -/// is no required relationship between the output of each; e.g. many -/// implementations of [`fill_bytes`] consume a whole number of `u32` or `u64` -/// values and drop any remaining unused bytes. -/// -/// The [`try_fill_bytes`] method is a variant of [`fill_bytes`] allowing error -/// handling; it is not deemed sufficiently useful to add equivalents for -/// [`next_u32`] or [`next_u64`] since the latter methods are almost always used -/// with algorithmic generators (PRNGs), which are normally infallible. -/// -/// Algorithmic generators implementing [`SeedableRng`] should normally have -/// *portable, reproducible* output, i.e. fix Endianness when converting values -/// to avoid platform differences, and avoid making any changes which affect -/// output (except by communicating that the release has breaking changes). -/// -/// Typically implementators will implement only one of the methods available -/// in this trait directly, then use the helper functions from the -/// [`impls`] module to implement the other methods. -/// -/// It is recommended that implementations also implement: -/// -/// - `Debug` with a custom implementation which *does not* print any internal -/// state (at least, [`CryptoRng`]s should not risk leaking state through -/// `Debug`). -/// - `Serialize` and `Deserialize` (from Serde), preferably making Serde -/// support optional at the crate level in PRNG libs. -/// - `Clone`, if possible. -/// - *never* implement `Copy` (accidental copies may cause repeated values). -/// - *do not* implement `Default` for pseudorandom generators, but instead -/// implement [`SeedableRng`], to guide users towards proper seeding. -/// External / hardware RNGs can choose to implement `Default`. -/// - `Eq` and `PartialEq` could be implemented, but are probably not useful. -/// -/// # Example -/// -/// A simple example, obviously not generating very *random* output: -/// -/// ``` -/// #![allow(dead_code)] -/// use rand_core::{RngCore, Error, impls}; -/// -/// struct CountingRng(u64); -/// -/// impl RngCore for CountingRng { -/// fn next_u32(&mut self) -> u32 { -/// self.next_u64() as u32 -/// } -/// -/// fn next_u64(&mut self) -> u64 { -/// self.0 += 1; -/// self.0 -/// } -/// -/// fn fill_bytes(&mut self, dest: &mut [u8]) { -/// impls::fill_bytes_via_next(self, dest) -/// } -/// -/// fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> { -/// Ok(self.fill_bytes(dest)) -/// } -/// } -/// ``` -/// -/// [`rand`]: https://docs.rs/rand -/// [`try_fill_bytes`]: RngCore::try_fill_bytes -/// [`fill_bytes`]: RngCore::fill_bytes -/// [`next_u32`]: RngCore::next_u32 -/// [`next_u64`]: RngCore::next_u64 -pub trait RngCore { - /// Return the next random `u32`. - /// - /// RNGs must implement at least one method from this trait directly. In - /// the case this method is not implemented directly, it can be implemented - /// using `self.next_u64() as u32` or via - /// [`fill_bytes`](impls::next_u32_via_fill). - fn next_u32(&mut self) -> u32; - - /// Return the next random `u64`. - /// - /// RNGs must implement at least one method from this trait directly. In - /// the case this method is not implemented directly, it can be implemented - /// via [`next_u32`](impls::next_u64_via_u32) or via - /// [`fill_bytes`](impls::next_u64_via_fill). - fn next_u64(&mut self) -> u64; - - /// Fill `dest` with random data. - /// - /// RNGs must implement at least one method from this trait directly. In - /// the case this method is not implemented directly, it can be implemented - /// via [`next_u*`](impls::fill_bytes_via_next) or - /// via [`try_fill_bytes`](RngCore::try_fill_bytes); if this generator can - /// fail the implementation must choose how best to handle errors here - /// (e.g. panic with a descriptive message or log a warning and retry a few - /// times). - /// - /// This method should guarantee that `dest` is entirely filled - /// with new data, and may panic if this is impossible - /// (e.g. reading past the end of a file that is being used as the - /// source of randomness). - fn fill_bytes(&mut self, dest: &mut [u8]); - - /// Fill `dest` entirely with random data. - /// - /// This is the only method which allows an RNG to report errors while - /// generating random data thus making this the primary method implemented - /// by external (true) RNGs (e.g. `OsRng`) which can fail. It may be used - /// directly to generate keys and to seed (infallible) PRNGs. - /// - /// Other than error handling, this method is identical to [`fill_bytes`]; - /// thus this may be implemented using `Ok(self.fill_bytes(dest))` or - /// `fill_bytes` may be implemented with - /// `self.try_fill_bytes(dest).unwrap()` or more specific error handling. - /// - /// [`fill_bytes`]: RngCore::fill_bytes - fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error>; -} - -/// A marker trait used to indicate that an [`RngCore`] or [`BlockRngCore`] -/// implementation is supposed to be cryptographically secure. -/// -/// *Cryptographically secure generators*, also known as *CSPRNGs*, should -/// satisfy an additional properties over other generators: given the first -/// *k* bits of an algorithm's output -/// sequence, it should not be possible using polynomial-time algorithms to -/// predict the next bit with probability significantly greater than 50%. -/// -/// Some generators may satisfy an additional property, however this is not -/// required by this trait: if the CSPRNG's state is revealed, it should not be -/// computationally-feasible to reconstruct output prior to this. Some other -/// generators allow backwards-computation and are consided *reversible*. -/// -/// Note that this trait is provided for guidance only and cannot guarantee -/// suitability for cryptographic applications. In general it should only be -/// implemented for well-reviewed code implementing well-regarded algorithms. -/// -/// Note also that use of a `CryptoRng` does not protect against other -/// weaknesses such as seeding from a weak entropy source or leaking state. -/// -/// [`BlockRngCore`]: block::BlockRngCore -pub trait CryptoRng {} - -/// A random number generator that can be explicitly seeded. -/// -/// This trait encapsulates the low-level functionality common to all -/// pseudo-random number generators (PRNGs, or algorithmic generators). -/// -/// [`rand`]: https://docs.rs/rand -pub trait SeedableRng: Sized { - /// Seed type, which is restricted to types mutably-dereferencable as `u8` - /// arrays (we recommend `[u8; N]` for some `N`). - /// - /// It is recommended to seed PRNGs with a seed of at least circa 100 bits, - /// which means an array of `[u8; 12]` or greater to avoid picking RNGs with - /// partially overlapping periods. - /// - /// For cryptographic RNG's a seed of 256 bits is recommended, `[u8; 32]`. - /// - /// - /// # Implementing `SeedableRng` for RNGs with large seeds - /// - /// Note that the required traits `core::default::Default` and - /// `core::convert::AsMut<u8>` are not implemented for large arrays - /// `[u8; N]` with `N` > 32. To be able to implement the traits required by - /// `SeedableRng` for RNGs with such large seeds, the newtype pattern can be - /// used: - /// - /// ``` - /// use rand_core::SeedableRng; - /// - /// const N: usize = 64; - /// pub struct MyRngSeed(pub [u8; N]); - /// pub struct MyRng(MyRngSeed); - /// - /// impl Default for MyRngSeed { - /// fn default() -> MyRngSeed { - /// MyRngSeed([0; N]) - /// } - /// } - /// - /// impl AsMut<[u8]> for MyRngSeed { - /// fn as_mut(&mut self) -> &mut [u8] { - /// &mut self.0 - /// } - /// } - /// - /// impl SeedableRng for MyRng { - /// type Seed = MyRngSeed; - /// - /// fn from_seed(seed: MyRngSeed) -> MyRng { - /// MyRng(seed) - /// } - /// } - /// ``` - type Seed: Sized + Default + AsMut<[u8]>; - - /// Create a new PRNG using the given seed. - /// - /// PRNG implementations are allowed to assume that bits in the seed are - /// well distributed. That means usually that the number of one and zero - /// bits are roughly equal, and values like 0, 1 and (size - 1) are unlikely. - /// Note that many non-cryptographic PRNGs will show poor quality output - /// if this is not adhered to. If you wish to seed from simple numbers, use - /// `seed_from_u64` instead. - /// - /// All PRNG implementations should be reproducible unless otherwise noted: - /// given a fixed `seed`, the same sequence of output should be produced - /// on all runs, library versions and architectures (e.g. check endianness). - /// Any "value-breaking" changes to the generator should require bumping at - /// least the minor version and documentation of the change. - /// - /// It is not required that this function yield the same state as a - /// reference implementation of the PRNG given equivalent seed; if necessary - /// another constructor replicating behaviour from a reference - /// implementation can be added. - /// - /// PRNG implementations should make sure `from_seed` never panics. In the - /// case that some special values (like an all zero seed) are not viable - /// seeds it is preferable to map these to alternative constant value(s), - /// for example `0xBAD5EEDu32` or `0x0DDB1A5E5BAD5EEDu64` ("odd biases? bad - /// seed"). This is assuming only a small number of values must be rejected. - fn from_seed(seed: Self::Seed) -> Self; - - /// Create a new PRNG using a `u64` seed. - /// - /// This is a convenience-wrapper around `from_seed` to allow construction - /// of any `SeedableRng` from a simple `u64` value. It is designed such that - /// low Hamming Weight numbers like 0 and 1 can be used and should still - /// result in good, independent seeds to the PRNG which is returned. - /// - /// This **is not suitable for cryptography**, as should be clear given that - /// the input size is only 64 bits. - /// - /// Implementations for PRNGs *may* provide their own implementations of - /// this function, but the default implementation should be good enough for - /// all purposes. *Changing* the implementation of this function should be - /// considered a value-breaking change. - fn seed_from_u64(mut state: u64) -> Self { - // We use PCG32 to generate a u32 sequence, and copy to the seed - const MUL: u64 = 6364136223846793005; - const INC: u64 = 11634580027462260723; - - let mut seed = Self::Seed::default(); - for chunk in seed.as_mut().chunks_mut(4) { - // We advance the state first (to get away from the input value, - // in case it has low Hamming Weight). - state = state.wrapping_mul(MUL).wrapping_add(INC); - - // Use PCG output function with to_le to generate x: - let xorshifted = (((state >> 18) ^ state) >> 27) as u32; - let rot = (state >> 59) as u32; - let x = xorshifted.rotate_right(rot).to_le(); - - unsafe { - let p = &x as *const u32 as *const u8; - copy_nonoverlapping(p, chunk.as_mut_ptr(), chunk.len()); - } - } - - Self::from_seed(seed) - } - - /// Create a new PRNG seeded from another `Rng`. - /// - /// This may be useful when needing to rapidly seed many PRNGs from a master - /// PRNG, and to allow forking of PRNGs. It may be considered deterministic. - /// - /// The master PRNG should be at least as high quality as the child PRNGs. - /// When seeding non-cryptographic child PRNGs, we recommend using a - /// different algorithm for the master PRNG (ideally a CSPRNG) to avoid - /// correlations between the child PRNGs. If this is not possible (e.g. - /// forking using small non-crypto PRNGs) ensure that your PRNG has a good - /// mixing function on the output or consider use of a hash function with - /// `from_seed`. - /// - /// Note that seeding `XorShiftRng` from another `XorShiftRng` provides an - /// extreme example of what can go wrong: the new PRNG will be a clone - /// of the parent. - /// - /// PRNG implementations are allowed to assume that a good RNG is provided - /// for seeding, and that it is cryptographically secure when appropriate. - /// As of `rand` 0.7 / `rand_core` 0.5, implementations overriding this - /// method should ensure the implementation satisfies reproducibility - /// (in prior versions this was not required). - /// - /// [`rand`]: https://docs.rs/rand - /// [`rand_os`]: https://docs.rs/rand_os - fn from_rng<R: RngCore>(mut rng: R) -> Result<Self, Error> { - let mut seed = Self::Seed::default(); - rng.try_fill_bytes(seed.as_mut())?; - Ok(Self::from_seed(seed)) - } - - /// Creates a new instance of the RNG seeded via [`getrandom`]. - /// - /// This method is the recommended way to construct non-deterministic PRNGs - /// since it is convenient and secure. - /// - /// In case the overhead of using [`getrandom`] to seed *many* PRNGs is an - /// issue, one may prefer to seed from a local PRNG, e.g. - /// `from_rng(thread_rng()).unwrap()`. - /// - /// # Panics - /// - /// If [`getrandom`] is unable to provide secure entropy this method will panic. - /// - /// [`getrandom`]: https://docs.rs/getrandom - #[cfg(feature="getrandom")] - fn from_entropy() -> Self { - let mut seed = Self::Seed::default(); - if let Err(err) = getrandom::getrandom(seed.as_mut()) { - panic!("from_entropy failed: {}", err); - } - Self::from_seed(seed) - } -} - -// Implement `RngCore` for references to an `RngCore`. -// Force inlining all functions, so that it is up to the `RngCore` -// implementation and the optimizer to decide on inlining. -impl<'a, R: RngCore + ?Sized> RngCore for &'a mut R { - #[inline(always)] - fn next_u32(&mut self) -> u32 { - (**self).next_u32() - } - - #[inline(always)] - fn next_u64(&mut self) -> u64 { - (**self).next_u64() - } - - #[inline(always)] - fn fill_bytes(&mut self, dest: &mut [u8]) { - (**self).fill_bytes(dest) - } - - #[inline(always)] - fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> { - (**self).try_fill_bytes(dest) - } -} - -// Implement `RngCore` for boxed references to an `RngCore`. -// Force inlining all functions, so that it is up to the `RngCore` -// implementation and the optimizer to decide on inlining. -#[cfg(feature="alloc")] -impl<R: RngCore + ?Sized> RngCore for Box<R> { - #[inline(always)] - fn next_u32(&mut self) -> u32 { - (**self).next_u32() - } - - #[inline(always)] - fn next_u64(&mut self) -> u64 { - (**self).next_u64() - } - - #[inline(always)] - fn fill_bytes(&mut self, dest: &mut [u8]) { - (**self).fill_bytes(dest) - } - - #[inline(always)] - fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> { - (**self).try_fill_bytes(dest) - } -} - -#[cfg(feature="std")] -impl std::io::Read for dyn RngCore { - fn read(&mut self, buf: &mut [u8]) -> Result<usize, std::io::Error> { - self.try_fill_bytes(buf)?; - Ok(buf.len()) - } -} - -// Implement `CryptoRng` for references to an `CryptoRng`. -impl<'a, R: CryptoRng + ?Sized> CryptoRng for &'a mut R {} - -// Implement `CryptoRng` for boxed references to an `CryptoRng`. -#[cfg(feature="alloc")] -impl<R: CryptoRng + ?Sized> CryptoRng for Box<R> {} - -#[cfg(test)] -mod test { - use super::*; - - #[test] - fn test_seed_from_u64() { - struct SeedableNum(u64); - impl SeedableRng for SeedableNum { - type Seed = [u8; 8]; - fn from_seed(seed: Self::Seed) -> Self { - let mut x = [0u64; 1]; - le::read_u64_into(&seed, &mut x); - SeedableNum(x[0]) - } - } - - const N: usize = 8; - const SEEDS: [u64; N] = [0u64, 1, 2, 3, 4, 8, 16, -1i64 as u64]; - let mut results = [0u64; N]; - for (i, seed) in SEEDS.iter().enumerate() { - let SeedableNum(x) = SeedableNum::seed_from_u64(*seed); - results[i] = x; - } - - for (i1, r1) in results.iter().enumerate() { - let weight = r1.count_ones(); - // This is the binomial distribution B(64, 0.5), so chance of - // weight < 20 is binocdf(19, 64, 0.5) = 7.8e-4, and same for - // weight > 44. - assert!(weight >= 20 && weight <= 44); - - for (i2, r2) in results.iter().enumerate() { - if i1 == i2 { continue; } - let diff_weight = (r1 ^ r2).count_ones(); - assert!(diff_weight >= 20); - } - } - - // value-breakage test: - assert_eq!(results[0], 5029875928683246316); - } -} |