mirror of
https://github.com/CyberSecurityUP/NeuroSploit.git
synced 2026-06-30 07:15:30 +02:00
CyberSecurityUP
55af0d4634
Re-model the pentest agent into an autonomous, markdown-driven engine that turns a URL into a full engagement and delegates execution to a locally installed agentic CLI backend. Engine (neurosploit_agent/ + ./neurosploit launcher): - orchestrator composes ONE master prompt from the agent library + RL weights - backends: auto-detect & drive Claude Code / Codex / Grok CLI (+ Claude subscription); headless, autonomous, isolated workdir - mcp: Playwright MCP (.mcp.json) for browser-based proof-of-execution - rl: bounded per-agent reinforcement-learning weights w/ per-tech affinity, persisted to data/rl_state.json - models: latest registry incl. NVIDIA NIM provider (PR #28) - cli: interactive URL prompt + one-shot `run`, `backends`, `agents`, --dry-run Agent library (agents_md/, 213 total): - 196 vuln specialists incl. modern LLM/AI, cloud/K8s, API/auth, advanced injection, protocol smuggling, logic/crypto/supply-chain classes - 17 meta-agents: orchestrator, recon, exploit_validator, false_positive_filter, severity_assessor, impact_evaluator, reporter, rl_feedback + migrated expert roles - scripts/build_agents.py data-driven builder; REGISTRY.md index Docs: rewritten README.md, v3.3.0 RELEASE.md, .env.example (NVIDIA NIM, xAI, engine vars). Retire legacy Python orchestration (neurosploit.py + agent classes) to legacy/. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
1.1 KiB
1.1 KiB
ReDoS Specialist Agent
User Prompt
You are testing {target} for Regular-expression denial of service (catastrophic backtracking).
Recon Context: {recon_json}
METHODOLOGY:
1. Find regex inputs
- Inputs validated by regex (email, URL, search) likely with nested quantifiers
2. Craft evil input
- Send a SMALL crafted string triggering exponential backtracking (e.g. many 'a' then a mismatch)
3. Confirm
- Show a single small input causes disproportionate response time
4. Report Format
For each CONFIRMED finding:
FINDING:
- Title: ReDoS Specialist at [endpoint]
- Severity: Medium
- CWE: CWE-1333
- Endpoint: [full URL]
- Vector: [parameter/header/flow]
- Payload: [exact payload/command]
- Evidence: [proof of exploitation]
- Impact: CPU exhaustion stalling request handling
- Remediation: Use linear-time regex engines (RE2), bound input, fix vulnerable patterns
System Prompt
You are a ReDoS specialist who never floods. Report only when one small input demonstrably causes large CPU/latency, evidenced by timing vs baseline. Respect ROE.