wafrift-strategy 0.3.1

Evasion strategy pipeline — orchestrates all WAF Rift modules into a coherent evasion flow.
Documentation 
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//! wafrift-strategy — Evasion strategy pipeline.
//!
//! The orchestrator that wires all WAF Rift modules into a coherent
//! evasion flow: request → detect → grammar → encoding →
//! content-type → smuggling → fingerprint → result.
//!
//! Maintains per-host adaptive state (`HostState`), promotes proven-winner
//! techniques into a rotation pool, evicts winners that get blocked, and
//! restarts full discovery when all winners are exhausted. Per-WAF state
//! persists to `~/.wafrift/genomes/<waf>.json` across sessions.
//! Also integrates MCTS (`mcts_bridge`) and ML-WAF evasion (`ml_evasion`).
//!
//! # Examples
//!
//! Per-host adaptation: the strategy keeps a [`HostState`] for each
//! target. As blocks pile up the engine escalates encoding choices;
//! once a technique consistently bypasses, it gets promoted to a
//! "proven winner" and the engine rotates through the winner pool
//! instead of re-discovering from scratch.
//!
//! ```
//! use wafrift_strategy::HostState;
//! use wafrift_types::technique::Technique;
//!
//! let mut state = HostState::default();
//! assert!(!state.waf_confirmed);
//! assert_eq!(state.blocks, 0);
//!
//! // Three confirmed blocks — strategy now knows escalation is needed.
//! state.record_block();
//! state.record_block();
//! state.record_block();
//! assert_eq!(state.blocks, 3);
//! assert!(state.needs_evasion());
//!
//! // After a single technique succeeds, last_success is populated and
//! // the per-technique success rate gets tracked for future rotation.
//! state.record_success(Technique::HeaderObfuscation("uppercase".into()));
//! assert!(state.last_success.is_some());
//! ```

pub mod composition;
pub mod cost;
/// Drift-aware evasion window detection (#115).
/// CUSUM-based sequential change-point detector for WAF regime shifts.
pub mod drift_window;
pub mod gene_bank;
pub mod host_state;
pub mod learning_cache;
/// MCTS bridge for intelligent evasion trajectory optimization.
pub mod mcts_bridge;
/// ML-WAF evasion routing (#129): decision-based boundary attack for learned
/// classifiers (AWS Bot Control, Cloudflare Bot Management, Akamai Bot Manager).
pub mod ml_evasion;
pub mod pipeline;
pub mod planner;
pub mod strategy;
/// WAF-specific evasion presets loaded from TOML rules.
pub mod waf_presets;

pub use drift_window::{
    BypassRateMonitor, ChangePointEvent, DriftDetector, ProbeObservation, RegimeChange,
};
pub use host_state::HostState;
pub use learning_cache::LearningCache;
pub use ml_evasion::{DEFAULT_ML_BUDGET, apply_ml_evasion_if_applicable};
pub use pipeline::{EvasionPipeline, EvasionPlanOutput};
pub use planner::plan_pipelines;
pub use strategy::*;

pub mod explain;
/// Plugin bridge — integrates external TOML/WASM tampers from wafrift-plugin-api
/// into the evasion pipeline alongside built-in tampers.
pub mod plugin_bridge;