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Diffstat (limited to 'rand/rand_core/src/lib.rs')
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diff --git a/rand/rand_core/src/lib.rs b/rand/rand_core/src/lib.rs new file mode 100644 index 0000000..a65db93 --- /dev/null +++ b/rand/rand_core/src/lib.rs @@ -0,0 +1,486 @@ +// 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://crates.io/crates/rand +//! [`RngCore`]: trait.RngCore.html +//! [`SeedableRng`]: trait.SeedableRng.html +//! [`Error`]: struct.Error.html +//! [`impls`]: impls/index.html +//! [`le`]: le/index.html + +#![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))))] + +#![cfg_attr(not(feature="std"), no_std)] +#![cfg_attr(all(feature="alloc", not(feature="std")), feature(alloc))] + +#[cfg(feature="std")] extern crate core; +#[cfg(all(feature = "alloc", not(feature="std")))] extern crate alloc; +#[cfg(feature="serde1")] extern crate serde; +#[cfg(feature="serde1")] #[macro_use] extern crate serde_derive; + + +use core::default::Default; +use core::convert::AsMut; +use core::ptr::copy_nonoverlapping; + +#[cfg(all(feature="alloc", not(feature="std")))] use alloc::boxed::Box; + +pub use error::{ErrorKind, Error}; + + +mod error; +pub mod block; +pub mod impls; +pub mod le; + + +/// 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 [`Rng`] 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 +/// [`rand_core::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://crates.io/crates/rand +/// [`Rng`]: ../rand/trait.Rng.html +/// [`SeedableRng`]: trait.SeedableRng.html +/// [`rand_core::impls`]: ../rand_core/impls/index.html +/// [`try_fill_bytes`]: trait.RngCore.html#tymethod.try_fill_bytes +/// [`fill_bytes`]: trait.RngCore.html#tymethod.fill_bytes +/// [`next_u32`]: trait.RngCore.html#tymethod.next_u32 +/// [`next_u64`]: trait.RngCore.html#tymethod.next_u64 +/// [`CryptoRng`]: trait.CryptoRng.html +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`](../rand_core/impls/fn.next_u32_via_fill.html). + 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`](../rand_core/impls/fn.next_u64_via_u32.html) or + /// [via `fill_bytes`](../rand_core/impls/fn.next_u64_via_fill.html). + 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*`](../rand_core/impls/fn.fill_bytes_via_next.html) or + /// via `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`]: trait.RngCore.html#method.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. +/// +/// [`RngCore`]: trait.RngCore.html +/// [`BlockRngCore`]: ../rand_core/block/trait.BlockRngCore.html +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). +/// +/// The [`rand::FromEntropy`] trait is automatically implemented for every type +/// implementing `SeedableRng`, providing a convenient `from_entropy()` +/// constructor. +/// +/// [`rand::FromEntropy`]: ../rand/trait.FromEntropy.html +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 about equal, and values like 0, 1 and (size - 1) are unlikely. + /// + /// PRNG implementations are recommended to be reproducible. A PRNG seeded + /// using this function with a fixed seed should produce the same sequence + /// of output in the future and on different architectures (with for example + /// different endianness). + /// + /// It is however 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 is the recommended way to initialize PRNGs with fresh entropy. The + /// [`FromEntropy`] trait provides a convenient `from_entropy` method + /// based on `from_rng`. + /// + /// Usage of this method is not recommended when reproducibility is required + /// since implementing PRNGs are not required to fix Endianness and are + /// allowed to modify implementations in new releases. + /// + /// It is important to use a good source of randomness to initialize the + /// PRNG. Cryptographic PRNG may be rendered insecure when seeded from a + /// non-cryptographic PRNG or with insufficient entropy. + /// Many non-cryptographic PRNGs will show statistical bias in their first + /// results if their seed numbers are small or if there is a simple pattern + /// between them. + /// + /// Prefer to seed from a strong external entropy source like [`OsRng`] or + /// from a cryptographic PRNG; if creating a new generator for cryptographic + /// uses you *must* seed from a strong source. + /// + /// Seeding a small PRNG from another small PRNG is possible, but + /// something to be careful with. An extreme example of how this can go + /// wrong is seeding an Xorshift RNG from another Xorshift RNG, which + /// will effectively clone the generator. In general seeding from a + /// generator which is hard to predict is probably okay. + /// + /// PRNG implementations are allowed to assume that a good RNG is provided + /// for seeding, and that it is cryptographically secure when appropriate. + /// + /// [`FromEntropy`]: ../rand/trait.FromEntropy.html + /// [`OsRng`]: ../rand/rngs/struct.OsRng.html + 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)) + } +} + +// 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 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); + } +} |