Cover image

Bloodhound-MCP-AI ist eine Integration, die Bluthund mit AI durch Modellkontextprotokoll verbindet und es Sicherheitsprofis ermöglicht, Active Directory-Angriffswege mit natürlicher Sprache anstelle komplexer Cypher-Abfragen zu analysieren.

3 years

Works with Finder

1

Github Watches

6

Github Forks

57

Github Stars

BloodHound-MCP

BloodHound-MCP

Model Context Protocol (MCP) Server for BloodHound

BloodHound-MCP is a powerful integration that brings the capabilities of Model Context Procotol (MCP) Server to BloodHound, the industry-standard tool for Active Directory security analysis. This integration allows you to analyze BloodHound data using natural language, making complex Active Directory attack path analysis accessible to everyone.

🥇 First-Ever BloodHound AI Integration!
This is the first integration that connects BloodHound with AI through MCP, originally announced here.

🔍 What is BloodHound-MCP?

BloodHound-MCP combines the power of:

  • BloodHound: Industry-standard tool for visualizing and analyzing Active Directory attack paths
  • Model Context Protocol (MCP): An open protocol for creating custom AI tools, compatible with various AI models
  • Neo4j: Graph database used by BloodHound to store AD relationship data

With over 75 specialized tools based on the original BloodHound CE Cypher queries, BloodHound-MCP allows security professionals to:

  • Query BloodHound data using natural language
  • Discover complex attack paths in Active Directory environments
  • Assess Active Directory security posture more efficiently
  • Generate detailed security reports for stakeholders

📱 Community

Join our Telegram channel for updates, tips, and discussion:

✨ Features

  • Natural Language Interface: Query BloodHound data using plain English
  • Comprehensive Analysis Categories:
    • Domain structure mapping
    • Privilege escalation paths
    • Kerberos security issues (Kerberoasting, AS-REP Roasting)
    • Certificate services vulnerabilities
    • Active Directory hygiene assessment
    • NTLM relay attack vectors
    • Delegation abuse opportunities
    • And much more!

📋 Prerequisites

  • BloodHound 4.x+ with data collected from an Active Directory environment
  • Neo4j database with BloodHound data loaded
  • Python 3.8 or higher
  • MCP Client

🔧 Installation

  1. Clone this repository:

    git clone https://github.com/your-username/MCP-BloodHound.git
    cd MCP-BloodHound
    
  2. Install dependencies:

    pip install -r requirements.txt
    
  3. Configure the MCP Server

    "mcpServers": {
        "BloodHound-MCP": {
            "command": "python",
            "args": [
                "<Your_Path>\\BloodHound-MCP.py"
            ],
            "env": {
                "BLOODHOUND_URI": "bolt://localhost:7687",
                "BLOODHOUND_USERNAME": "neo4j",
                "BLOODHOUND_PASSWORD": "bloodhoundcommunityedition"
            }
        }
    }
    

🚀 Usage

Example queries you can ask through the MCP:

  • "Show me all paths from kerberoastable users to Domain Admins"
  • "Find computers where Domain Users have local admin rights"
  • "Identify Domain Controllers vulnerable to NTLM relay attacks"
  • "Map all Active Directory certificate services vulnerabilities"
  • "Generate a comprehensive security report for my domain"
  • "Find inactive privileged accounts"
  • "Show me attack paths to high-value targets"

🔐 Security Considerations

This tool is designed for legitimate security assessment purposes. Always:

  • Obtain proper authorization before analyzing any Active Directory environment
  • Handle BloodHound data as sensitive information
  • Follow responsible disclosure practices for any vulnerabilities discovered

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

  • The BloodHound team for creating an amazing Active Directory security tool
  • The security community for continuously advancing AD security practices

Note: This is not an official Anthropic product. BloodHound-MCP is a community-driven integration between BloodHound and MCP.

相关推荐

  • Joshua Armstrong
  • Confidential guide on numerology and astrology, based of GG33 Public information

  • https://suefel.com
  • Latest advice and best practices for custom GPT development.

  • Emmet Halm
  • Converts Figma frames into front-end code for various mobile frameworks.

  • Elijah Ng Shi Yi
  • Advanced software engineer GPT that excels through nailing the basics.

  • https://maiplestudio.com
  • Find Exhibitors, Speakers and more

  • lumpenspace
  • Take an adjectivised noun, and create images making it progressively more adjective!

  • https://appia.in
  • Siri Shortcut Finder – your go-to place for discovering amazing Siri Shortcuts with ease

  • Carlos Ferrin
  • Encuentra películas y series en plataformas de streaming.

  • Yusuf Emre Yeşilyurt
  • I find academic articles and books for research and literature reviews.

  • tomoyoshi hirata
  • Sony α7IIIマニュアルアシスタント

  • apappascs
  • Entdecken Sie die umfassendste und aktuellste Sammlung von MCP-Servern auf dem Markt. Dieses Repository dient als zentraler Hub und bietet einen umfangreichen Katalog von Open-Source- und Proprietary MCP-Servern mit Funktionen, Dokumentationslinks und Mitwirkenden.

  • jae-jae
  • MCP -Server für den Fetch -Webseiteninhalt mit dem Headless -Browser von Dramatikern.

  • ravitemer
  • Ein leistungsstarkes Neovim -Plugin für die Verwaltung von MCP -Servern (Modellkontextprotokoll)

  • patruff
  • Brücke zwischen Ollama und MCP -Servern und ermöglicht es lokalen LLMs, Modellkontextprotokoll -Tools zu verwenden

  • pontusab
  • Die Cursor & Windsurf -Community finden Regeln und MCPs

  • av
  • Führen Sie mühelos LLM -Backends, APIs, Frontends und Dienste mit einem Befehl aus.

  • WangRongsheng
  • 🧑‍🚀 全世界最好的 llm 资料总结(数据处理、模型训练、模型部署、 O1 模型、 MCP 、小语言模型、视觉语言模型) | Zusammenfassung der weltbesten LLM -Ressourcen.

  • Mintplex-Labs
  • Die All-in-One-Desktop & Docker-AI-Anwendung mit integriertem Lappen, AI-Agenten, No-Code-Agent Builder, MCP-Kompatibilität und vielem mehr.

  • appcypher
  • Awesome MCP -Server - eine kuratierte Liste von Modellkontext -Protokollservern für Modellkontext

    Reviews

    2 (1)
    Avatar
    user_qHx2KDN7
    2025-04-17

    As a dedicated user of BloodHound-MCP-AI, I can confidently say that this tool has revolutionized my approach to network analysis and penetration testing. MorDavid has created an exceptional AI-driven platform that is both intuitive and powerful. For anyone serious about cybersecurity, I highly recommend exploring this remarkable tool.