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cli/vendor/quinn-proto/src/bloom_token_log.rs

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use std::{
collections::HashSet,
f64::consts::LN_2,
hash::{BuildHasher, Hasher},
mem::{size_of, take},
sync::Mutex,
};
use fastbloom::BloomFilter;
use rustc_hash::FxBuildHasher;
use tracing::{trace, warn};
use crate::{Duration, SystemTime, TokenLog, TokenReuseError, UNIX_EPOCH};
/// Bloom filter-based [`TokenLog`]
///
/// Parameterizable over an approximate maximum number of bytes to allocate. Starts out by storing
/// used tokens in a hash set. Once the hash set becomes too large, converts it to a bloom filter.
/// This achieves a memory profile of linear growth with an upper bound.
///
/// Divides time into periods based on `lifetime` and stores two filters at any given moment, for
/// each of the two periods currently non-expired tokens could expire in. As such, turns over
/// filters as time goes on to avoid bloom filter false positive rate increasing infinitely over
/// time.
pub struct BloomTokenLog(Mutex<State>);
impl BloomTokenLog {
/// Construct with an approximate maximum memory usage and expected number of validation token
/// usages per expiration period
///
/// Calculates the optimal bloom filter k number automatically.
pub fn new_expected_items(max_bytes: usize, expected_hits: u64) -> Self {
Self::new(max_bytes, optimal_k_num(max_bytes, expected_hits))
}
/// Construct with an approximate maximum memory usage and a [bloom filter k number][bloom]
///
/// [bloom]: https://en.wikipedia.org/wiki/Bloom_filter
///
/// If choosing a custom k number, note that `BloomTokenLog` always maintains two filters
/// between them and divides the allocation budget of `max_bytes` evenly between them. As such,
/// each bloom filter will contain `max_bytes * 4` bits.
pub fn new(max_bytes: usize, k_num: u32) -> Self {
Self(Mutex::new(State {
config: FilterConfig {
filter_max_bytes: max_bytes / 2,
k_num,
},
period_1_start: UNIX_EPOCH,
filter_1: Filter::default(),
filter_2: Filter::default(),
}))
}
}
impl TokenLog for BloomTokenLog {
fn check_and_insert(
&self,
nonce: u128,
issued: SystemTime,
lifetime: Duration,
) -> Result<(), TokenReuseError> {
trace!(%nonce, "check_and_insert");
if lifetime.is_zero() {
// avoid divide-by-zero if lifetime is zero
return Err(TokenReuseError);
}
let mut guard = self.0.lock().unwrap();
let state = &mut *guard;
// calculate how many periods past period 1 the token expires
let expires_at = issued + lifetime;
let Ok(periods_forward) = expires_at
.duration_since(state.period_1_start)
.map(|duration| duration.as_nanos() / lifetime.as_nanos())
else {
// shouldn't happen unless time travels backwards or lifetime changes or the current
// system time is before the Unix epoch
warn!("BloomTokenLog presented with token too far in past");
return Err(TokenReuseError);
};
// get relevant filter
let filter = match periods_forward {
0 => &mut state.filter_1,
1 => &mut state.filter_2,
2 => {
// turn over filter 1
state.filter_1 = take(&mut state.filter_2);
state.period_1_start += lifetime;
&mut state.filter_2
}
_ => {
// turn over both filters
state.filter_1 = Filter::default();
state.filter_2 = Filter::default();
state.period_1_start = expires_at;
&mut state.filter_1
}
};
// insert into the filter
//
// the token's nonce needs to guarantee uniqueness because of the role it plays in the
// encryption of the tokens, so it is 128 bits. but since the token log can tolerate false
// positives, we trim it down to 64 bits, which would still only have a small collision
// rate even at significant amounts of usage, while allowing us to store twice as many in
// the hash set variant.
//
// token nonce values are uniformly randomly generated server-side and cryptographically
// integrity-checked, so we don't need to employ secure hashing to trim it down to 64 bits,
// we can simply truncate.
//
// per the Rust reference, we can truncate by simply casting:
// https://doc.rust-lang.org/stable/reference/expressions/operator-expr.html#numeric-cast
filter.check_and_insert(nonce as u64, &state.config)
}
}
/// Default to 20 MiB max memory consumption and expected one million hits
///
/// With the default validation token lifetime of 2 weeks, this corresponds to one token usage per
/// 1.21 seconds.
impl Default for BloomTokenLog {
fn default() -> Self {
Self::new_expected_items(DEFAULT_MAX_BYTES, DEFAULT_EXPECTED_HITS)
}
}
/// Lockable state of [`BloomTokenLog`]
struct State {
config: FilterConfig,
// filter_1 covers tokens that expire in the period starting at period_1_start and extending
// lifetime after. filter_2 covers tokens for the next lifetime after that.
period_1_start: SystemTime,
filter_1: Filter,
filter_2: Filter,
}
/// Unchanging parameters governing [`Filter`] behavior
struct FilterConfig {
filter_max_bytes: usize,
k_num: u32,
}
/// Period filter within [`State`]
enum Filter {
Set(HashSet<u64, IdentityBuildHasher>),
Bloom(BloomFilter<FxBuildHasher>),
}
impl Filter {
fn check_and_insert(
&mut self,
fingerprint: u64,
config: &FilterConfig,
) -> Result<(), TokenReuseError> {
match self {
Self::Set(hset) => {
if !hset.insert(fingerprint) {
return Err(TokenReuseError);
}
if hset.capacity() * size_of::<u64>() <= config.filter_max_bytes {
return Ok(());
}
// convert to bloom
// avoid panicking if user passed in filter_max_bytes of 0. we document that this
// limit is approximate, so just fudge it up to 1.
let mut bloom = BloomFilter::with_num_bits((config.filter_max_bytes * 8).max(1))
.hasher(FxBuildHasher)
.hashes(config.k_num);
for item in &*hset {
bloom.insert(item);
}
*self = Self::Bloom(bloom);
}
Self::Bloom(bloom) => {
if bloom.insert(&fingerprint) {
return Err(TokenReuseError);
}
}
}
Ok(())
}
}
impl Default for Filter {
fn default() -> Self {
Self::Set(HashSet::default())
}
}
/// `BuildHasher` of `IdentityHasher`
#[derive(Default)]
struct IdentityBuildHasher;
impl BuildHasher for IdentityBuildHasher {
type Hasher = IdentityHasher;
fn build_hasher(&self) -> Self::Hasher {
IdentityHasher::default()
}
}
/// Hasher that is the identity operation--it assumes that exactly 8 bytes will be hashed, and the
/// resultant hash is those bytes as a `u64`
#[derive(Default)]
struct IdentityHasher {
data: [u8; 8],
#[cfg(debug_assertions)]
wrote_8_byte_slice: bool,
}
impl Hasher for IdentityHasher {
fn write(&mut self, bytes: &[u8]) {
#[cfg(debug_assertions)]
{
assert!(!self.wrote_8_byte_slice);
assert_eq!(bytes.len(), 8);
self.wrote_8_byte_slice = true;
}
self.data.copy_from_slice(bytes);
}
fn finish(&self) -> u64 {
#[cfg(debug_assertions)]
assert!(self.wrote_8_byte_slice);
u64::from_ne_bytes(self.data)
}
}
fn optimal_k_num(num_bytes: usize, expected_hits: u64) -> u32 {
// be more forgiving rather than panickey here. excessively high num_bits may occur if the user
// wishes it to be unbounded, so just saturate. expected_hits of 0 would cause divide-by-zero,
// so just fudge it up to 1 in that case.
let num_bits = (num_bytes as u64).saturating_mul(8);
let expected_hits = expected_hits.max(1);
// reference for this formula: https://programming.guide/bloom-filter-calculator.html
// optimal k = (m ln 2) / n
// wherein m is the number of bits, and n is the number of elements in the set.
//
// we also impose a minimum return value of 1, to avoid making the bloom filter entirely
// useless in the case that the user provided an absurdly high ratio of hits / bytes.
(((num_bits as f64 / expected_hits as f64) * LN_2).round() as u32).max(1)
}
// remember to change the doc comment for `impl Default for BloomTokenLog` if these ever change
const DEFAULT_MAX_BYTES: usize = 10 << 20;
const DEFAULT_EXPECTED_HITS: u64 = 1_000_000;
#[cfg(test)]
mod test {
use super::*;
use rand::prelude::*;
use rand_pcg::Pcg32;
fn new_rng() -> impl Rng {
Pcg32::from_seed(0xdeadbeefdeadbeefdeadbeefdeadbeef_u128.to_le_bytes())
}
#[test]
fn identity_hash_test() {
let mut rng = new_rng();
let builder = IdentityBuildHasher;
for _ in 0..100 {
let n = rng.random::<u64>();
let hash = builder.hash_one(n);
assert_eq!(hash, n);
}
}
#[test]
fn optimal_k_num_test() {
assert_eq!(optimal_k_num(10 << 20, 1_000_000), 58);
assert_eq!(optimal_k_num(10 << 20, 1_000_000_000_000_000), 1);
// assert that these don't panic:
optimal_k_num(10 << 20, 0);
optimal_k_num(usize::MAX, 1_000_000);
}
#[test]
fn bloom_token_log_conversion() {
let mut rng = new_rng();
let mut log = BloomTokenLog::new_expected_items(800, 200);
let issued = SystemTime::now();
let lifetime = Duration::from_secs(1_000_000);
for i in 0..200 {
let token = rng.random::<u128>();
let result = log.check_and_insert(token, issued, lifetime);
{
let filter = &log.0.lock().unwrap().filter_1;
if let Filter::Set(ref hset) = *filter {
assert!(hset.capacity() * size_of::<u64>() <= 800);
assert_eq!(hset.len(), i + 1);
assert!(result.is_ok());
} else {
assert!(i > 10, "definitely bloomed too early");
}
}
assert!(log.check_and_insert(token, issued, lifetime).is_err());
}
assert!(
matches!(log.0.get_mut().unwrap().filter_1, Filter::Bloom { .. }),
"didn't bloom"
);
}
#[test]
fn turn_over() {
let mut rng = new_rng();
let log = BloomTokenLog::new_expected_items(800, 200);
let lifetime = Duration::from_secs(1_000);
let mut old = Vec::default();
let mut accepted = 0;
for i in 0..200 {
let token = rng.random::<u128>();
let now = UNIX_EPOCH + lifetime * 10 + lifetime * i / 10;
let issued = now - lifetime.mul_f32(rng.random_range(0.0..3.0));
let result = log.check_and_insert(token, issued, lifetime);
if result.is_ok() {
accepted += 1;
}
old.push((token, issued));
let old_idx = rng.random_range(0..old.len());
let (old_token, old_issued) = old[old_idx];
assert!(
log.check_and_insert(old_token, old_issued, lifetime)
.is_err()
);
}
assert!(accepted > 0);
}
fn test_doesnt_panic(log: BloomTokenLog) {
let mut rng = new_rng();
let issued = SystemTime::now();
let lifetime = Duration::from_secs(1_000_000);
for _ in 0..200 {
let _ = log.check_and_insert(rng.random::<u128>(), issued, lifetime);
}
}
#[test]
fn max_bytes_zero() {
// "max bytes" is documented to be approximate. but make sure it doesn't panic.
test_doesnt_panic(BloomTokenLog::new_expected_items(0, 200));
}
#[test]
fn expected_hits_zero() {
test_doesnt_panic(BloomTokenLog::new_expected_items(100, 0));
}
#[test]
fn k_num_zero() {
test_doesnt_panic(BloomTokenLog::new(100, 0));
}
}