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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>
16 lines
604 B
Python
16 lines
604 B
Python
"""
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NeuroSploit v3.3.0 — Autonomous MD-Agent Engine.
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A lean orchestration layer that turns a URL into an autonomous penetration test:
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it composes a master prompt from the curated `agents_md/` markdown library and
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hands execution to a locally-installed agentic CLI backend (Claude Code, Codex,
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or Grok CLI), augmented with Playwright MCP, and learns across runs via a
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reinforcement-learning reward loop.
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This package replaces the legacy Python orchestration (`neurosploit.py` + heavy
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`core/` agents), which now lives under `legacy/` for reference.
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"""
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__version__ = "3.3.0"
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__all__ = ["__version__"]
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