FAQ (answers come from our records)
How do I install it?
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We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
first catalogued 2026-10-14;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
DarkMoon
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
Open-source autonomous AI penetration testing — finds, exploits and qualifies every vulnerability on your own infrastructure
**⭐ Star DarkMoon** · **🚀 Quick Start** · **🧩 Integrations** · **📊 Benchmark** · **🔒 Darkmoon Pro** · **▶️ Install & Run (OSS)** · **▶️ Demo (Pro)**
**DarkMoon is autonomous AI penetration testing for your own infrastructure.** Point it at an authorized target and it runs the whole assessment on its own, then documents every finding with the exact command and raw output.
- 🟢 **Truly open source.** GPLv3 and self-hosted, every agent's methodology is plain Markdown you can read, diff and fork.
- 🎯 **Finds AND proves.** Each vulnerability ships with the exact command and raw output (exploitation is agent-asserted; the Pro remediation retest is the machine-verified step), so there is almost nothing to triage.
- 🔒 **Runs on a local LLM + Privacy Gateway.** The gateway tokenizes your real IPs, hosts and credentials locally, so the model reasons on placeholders while real values stay on your perimeter.
- 🧩 **Everywhere you build.** Run it from GitHub, GitLab, Jenkins, VS Code, JetBrains, n8n, Grafana or Splunk — the open-source edition works with the CLI-based ones. See the integrations ↓
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See the open source engine (CLI)
The open source Darkmoon is a command line tool. This is what you get when you clone the repo. You launch an assessment from the command line and watch every agent, command and finding stream past in real time.
Kick off a run from the CLI. One TARGET line and DarkMoon takes over the whole assessment.
Autonomous agents reason and exploit, live in your terminal. Here a sub-agent flags CVE-2019-9978 and pivots straight to exploitation.
Recon and environment model. DarkMoon fingerprints the stack and confirms the attack surface before it strikes.
Live MCP stream. Every command the agent runs and its raw output, timestamped, with ./darkmoon.sh --log <session> .
Signal to agent dispatch. DarkMoon decides which specialist agents to deploy from exactly what it detects on the target.
**As featured in** Help Net Security · Cyber Security News · DevOps.com · SecurityBrief · LinuxLinks · IT Brief · ChannelLife
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Quick Start
install.sh configures your LLM provider interactively (no need to edit docker-compose.yml) and builds the full stack:
Supports **cloud providers** (Anthropic, OpenAI, OpenRouter…) and **local models** (Ollama, llama.cpp). Then run your first assessment and watch it live:
**Prerequisites:** Docker & Docker Compose, and an LLM API key (or a local model). GPU setup, environment variables and the full flags reference live in the Full Documentation.
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Feature grid
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|---|---|
| 🧠 **50 specialist agents** | One agentic system reasons, plans and dispatches specialist agents across every surface it discovers. |
| 🌐 **Every surface** | Web, APIs, Active Directory, Kubernetes, cloud (AWS, Azure, GCP), CI/CD, databases, IoT firmware and AI/LLM endpoints, chained end to end. |
| 🔒 **Privacy Gateway** | Reversible local tokenization turns real IPs, hosts, URLs and credentials into deterministic placeholders, rehydrated only locally at the moment a tool runs. |
| 🏠 **Local model** | Run the whole assessment on a local LLM (Ollama, llama.cpp) so your infrastructure values stay on your own perimeter. |
| 🧾 **Evidence, not scores** | Every finding ships with the exact command and raw output; the Pro retest re-runs the exploit to confirm a fix. |
| 🛡️ **Security by design** | The AI never runs a command directly, every action flows through a controlled, logged MCP interface. |
| 🤖 **Pentests your AI too** | A dedicated LLM agent probes AI/LLM inference endpoints for the OWASP LLM Top 10 with garak-backed probes. |
| ♾️ **CI/CD native** | Trigger a pentest in the pipeline and get findings back as artifacts. |
| 🔌 **MCP** | Orchestrate 140+ offensive tools over MCP. |
| 🔧 **Fix it (Pro)** | The paid Pro tier turns findings into human-reviewed pull requests, retested against the original exploit. |
Built for **security teams**, **DevSecOps engineers**, **red teamers** and **ethical hacking** professionals.
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🧩 DarkMoon everywhere
Run DarkMoon where you already build — in CI/CD, your IDE, automation and SecOps. Integrations marked **OSS + Pro** work with the open-source edition (local CLI + JSON); the Pro-only ones consume the DarkMoon Pro REST API (live dashboard, remediation→PR).