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CyberSecurityUP
5d83e8848e
- Task-based model ROUTER (recon/select prefer a fast model; exploit prefers primary; validate uses a different model than the finder) - ReAct doctrine injected into exploit prompts (Thought→Action→Observation, token-efficient) - Dedup: unique agents per run + findings deduped by CWE/endpoint/title (highest confidence kept) - Token economy: recon blob capped for selector + per-agent context - Configurable MCP: merge user mcp.servers.json into the pipeline's .mcp.json - +54 white-box/code-analysis agents (NoSQLi, LDAP/XPath, JWT-none, Java/.NET/PHP/Go/Node/Python specifics, SSTI, ReDoS, deserialization, etc.) → 303 agents total (78 code) - Credits: Joas A Santos & Red Team Leaders (CLI banner, interactive header, HTML+Typst report) - README: GitHub stars/forks badges, 60-second quick start, full API config steps, intuitive layout Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
26 lines
878 B
Rust
26 lines
878 B
Rust
//! NeuroSploit v3.4.1 harness — a robust multi-model runtime for the
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//! markdown-driven autonomous pentest engine.
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//!
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//! The harness loads the `agents_md/` library, drives a *pool* of LLM models
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//! (any OpenAI-compatible provider) with concurrency + provider failover, runs
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//! the specialist agents in parallel, then validates every candidate finding by
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//! **N-model voting** before scoring and reporting.
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pub mod agents;
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pub mod models;
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pub mod pipeline;
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pub mod pool;
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pub mod report;
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pub mod rl;
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pub mod types;
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pub use agents::{Agent, Library};
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pub use models::{
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cli_binary_for, ensure_playwright_mcp, installed_cli_backends, mcp_supported, provider_for,
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providers, write_mcp_config, ChatClient, ModelRef, Provider,
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};
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pub use pipeline::{run_whitebox, RunOutput};
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pub use pipeline::run;
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pub use pool::{ModelPool, Task};
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pub use types::{Finding, RunConfig};
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