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wafrift_evolution/search/
mod.rs

1//! Search algorithms for evolutionary WAF bypass discovery.
2
3use crate::evolution::{Chromosome, GenePool};
4use crate::types::{Budget, EvolutionError, OracleVerdict, SearchStats};
5use rand::rngs::StdRng;
6use std::cmp::Ordering;
7
8/// A candidate requested for evaluation, with a stable evaluation ID.
9#[derive(Debug, Clone)]
10pub struct EvalCandidate {
11    /// Stable ID used to correlate results.
12    pub id: u64,
13    /// The chromosome to evaluate.
14    pub chromosome: Chromosome,
15}
16
17/// Result of submitting evaluations back to the algorithm.
18#[derive(Debug, Clone, Copy, PartialEq, Eq)]
19pub enum SubmitResult {
20    /// The algorithm accepted all results.
21    Accepted,
22    /// Some evaluation IDs were unknown.
23    UnknownIds(usize),
24}
25
26/// Core trait implemented by all search algorithms.
27///
28/// Each algorithm manages its own internal state (population, archive,
29/// temperature, tabu list, etc.). The [`EvolutionEngine`](crate::evolution::EvolutionEngine)
30/// handles caching, budgeting, and batching on top of this trait.
31pub trait SearchAlgorithm: Send + Sync + std::fmt::Debug {
32    /// Algorithm name.
33    fn name(&self) -> &'static str;
34
35    /// Initialize the algorithm with a seed population.
36    fn initialize(&mut self, population: Vec<Chromosome>, gene_pool: &GenePool, rng: &mut StdRng);
37
38    /// Request up to `n` candidates for parallel evaluation.
39    ///
40    /// Returns candidates with stable IDs. The caller evaluates them and
41    /// later calls [`submit_evaluations`](SearchAlgorithm::submit_evaluations).
42    fn request_evaluations(&mut self, n: usize, rng: &mut StdRng) -> Vec<EvalCandidate>;
43
44    /// Submit evaluation results.
45    ///
46    /// The ID in each tuple must match an ID previously returned by
47    /// `request_evaluations`.
48    fn submit_evaluations(&mut self, results: Vec<(u64, OracleVerdict)>);
49
50    /// Check whether the algorithm thinks search should stop.
51    fn should_terminate(&self, stats: &SearchStats, budget: &Budget) -> bool;
52
53    /// Get the best chromosome found so far.
54    fn best(&self) -> Option<&Chromosome>;
55
56    /// Serialize internal state to bytes.
57    fn checkpoint(&self) -> Result<Vec<u8>, EvolutionError>;
58
59    /// Restore internal state from bytes.
60    fn restore(&mut self, bytes: &[u8]) -> Result<(), EvolutionError>;
61
62    /// Snapshot the algorithm's current "live" chromosomes — the set
63    /// the engine is actively searching from.
64    ///
65    /// Population-based algorithms (`NoveltySearch`, `MapElites`)
66    /// return their full pool. Single-state algorithms (`HillClimbing`,
67    /// `SimulatedAnnealing`, `TabuSearch`) return the singleton
68    /// current/best so the engine sees `len() == 1` and reports
69    /// "no pairwise diversity yet" rather than zero.
70    ///
71    /// Used by [`EvolutionEngine::diversity_score`](crate::evolution::EvolutionEngine::diversity_score)
72    /// to drive adaptive mutation pressure. Cloning is acceptable here
73    /// because callers run it at engine-tick rate, not per-evaluation.
74    fn population_snapshot(&self) -> Vec<Chromosome> {
75        self.best().cloned().into_iter().collect()
76    }
77
78    /// Deep-clone this algorithm into a fresh trait object.
79    ///
80    /// Audit (2026-05-10): pre-fix the trait had a default impl that
81    /// panicked with "must override". That panic was reachable from
82    /// any out-of-tree algorithm that forgot to override; calling
83    /// `clone_box` from the proxy path then aborted the whole evade
84    /// pipeline. The fix removes the default — the compiler now
85    /// enforces the override at build time instead.
86    fn clone_box(&self) -> Box<dyn SearchAlgorithm>;
87}
88
89/// Convert non-finite fitness values into a strict worst-case sentinel.
90///
91/// NaN and +/-inf break partial ordering semantics and can lock algorithms
92/// into never-accept states. Mapping them to `-inf` keeps comparisons total.
93#[must_use]
94pub(crate) fn comparable_fitness(value: f64) -> f64 {
95    if value.is_finite() {
96        value
97    } else {
98        f64::NEG_INFINITY
99    }
100}
101
102#[must_use]
103pub(crate) fn fitness_cmp(a: f64, b: f64) -> Ordering {
104    comparable_fitness(a)
105        .partial_cmp(&comparable_fitness(b))
106        .unwrap_or(Ordering::Equal)
107}
108
109pub mod hill_climb;
110pub mod map_elites;
111pub mod novelty;
112pub mod sim_anneal;
113pub mod tabu;
114
115pub use hill_climb::HillClimbing;
116pub use map_elites::MapElites;
117pub use novelty::NoveltySearch;
118pub use sim_anneal::SimulatedAnnealing;
119pub use tabu::TabuSearch;