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A comprehensive cybersecurity framework built with AI agents, PKI infrastructure, and Model Context Protocol (MCP) integration.

• AI-Powered Security Agents: Intelligent agents for PKI management, vulnerability assessment, and security analysis
• PKI Infrastructure: Complete Public Key Infrastructure with certificate lifecycle management
• MCP Integration: Model Context Protocol server for seamless AI tool integration
• Docker Deployment: Containerized deployment with Docker Compose
• Comprehensive Testing: Integration tests for all components
• Scalable Architecture: Modular design supporting multiple security domains

The framework consists of several key components:

1. AI Agents (agents/)

   • Base agent framework with memory and tool registry
   • PKI-specific agent for certificate management
   • Extensible architecture for additional security domains

2. Infrastructure (infrastructure/)

   • MCP server for AI tool integration
   • PostgreSQL database for data persistence
   • Docker Compose orchestration
   • Vault integration for secrets management

3. Compose for Agents (compose-for-agents/)

   • Collection of pre-built agent frameworks
   • Support for multiple AI frameworks (LangGraph, CrewAI, etc.)
   • Ready-to-use agent templates

👉 QUICKSTART GUIDE - Build your first security agent in 10 minutes!

The quickstart guide will walk you through:

• ✅ Setting up your first agent (5 minutes)
• ✅ Running interactive network scans
• ✅ Understanding the framework architecture
• ✅ Building custom security tools

For advanced users who want the complete infrastructure:

• Docker and Docker Compose
• Python 3.11+ (for development)
• Git

1. Clone the repository:

git clone https://github.com/Mkp-dev-portefolio/cybersecurity-framework.git cd cybersecurity-framework

2. Quick demo (recommended for first-time users):

# Install minimal dependencies pip install -r requirements-quickstart.txt # Run the interactive quickstart python run_quickstart.py

3. Full setup (for development):

# Create virtual environment python3 -m venv .venv source .venv/bin/activate # Install all dependencies pip install -r requirements.txt # Start all services docker-compose -f infrastructure/docker-compose.yml up -d # Run tests pytest tests/test_mcp_integration.py -v

The PKI agent provides comprehensive certificate management capabilities:

from agents.pki.pki_agent import PKIAgent # Initialize the agent agent = PKIAgent() # Issue a certificate cert_request = { "common_name": "example.com", "organization": "My Organization", "country": "US" } certificate = agent.issue_certificate(cert_request) print(f"Certificate issued: {certificate['serial_number']}")

The MCP server provides AI tools for security operations:

# Start the MCP server cd infrastructure/mcp-server python src/main.py # The server will be available at http://localhost:8080

Deploy the entire framework using Docker Compose:

# Deploy all services docker-compose -f infrastructure/docker-compose.yml up -d # Scale specific services docker-compose -f infrastructure/docker-compose.yml up -d --scale mcp-server=3 # View logs docker-compose -f infrastructure/docker-compose.yml logs -f mcp-server

cybersecurity-framework/ ├── agents/ # AI agents │ ├── base/ # Base agent framework │ └── pki/ # PKI-specific agent ├── infrastructure/ # Core infrastructure │ ├── docker-compose.yml # Service orchestration │ ├── mcp-server/ # MCP server implementation │ └── postgres/ # Database configuration ├── compose-for-agents/ # Agent frameworks collection ├── tests/ # Integration tests ├── framework-structure.md # Architecture documentation └── README.md # This file 

1. Create a new agent directory under agents/
2. Implement the agent class inheriting from BaseAgent
3. Add tools and capabilities specific to your domain
4. Update the tool registry
5. Add tests for the new agent

# Run all tests pytest tests/ -v # Run specific test file pytest tests/test_mcp_integration.py -v # Run with coverage pytest tests/ --cov=agents --cov=infrastructure

Create a .env file in the root directory:

# Database POSTGRES_DB=cybersecurity_db POSTGRES_USER=cyber_user POSTGRES_PASSWORD=secure_password # MCP Server MCP_SERVER_PORT=8080 MCP_SERVER_HOST=0.0.0.0 # Vault (if using) VAULT_ADDR=http://localhost:8200 VAULT_TOKEN=your_vault_token

Each service can be configured through environment variables or configuration files:

• MCP Server: infrastructure/mcp-server/src/config.py
• Database: infrastructure/postgres/init.sql
• Agents: Individual agent configuration files

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

• Follow PEP 8 style guidelines
• Add tests for new features
• Update documentation for API changes
• Use type hints where appropriate
• Add docstrings for all functions and classes

• All sensitive data is encrypted at rest
• Certificate private keys are stored securely
• API endpoints are protected with authentication
• Regular security audits are performed
• Secrets are managed through environment variables

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

For support and questions:

• Open an issue on GitHub
• Check the documentation in framework-structure.md
• Review the test cases for usage examples

• Additional AI agent types (vulnerability scanning, compliance checking)
• Web UI for agent management
• Advanced analytics and reporting
• Integration with external security tools
• Multi-tenant support
• Enhanced monitoring and alerting

• Built with Model Context Protocol (MCP)
• Uses Docker for containerization
• Leverages modern AI frameworks
• Incorporates security best practices