Cybersecurity AI (CAI) is an open-source framework designed to build bug bounty-ready AI agents for cybersecurity tasks. It aims to democratize access to advanced AI security tools, empowering researchers and ethical hackers to automate and enhance various stages of penetration testing, from reconnaissance to vulnerability validation.

How It Works

CAI is built around an agent-centric design, abstracting cybersecurity behaviors into Agents that interact with environments using the ReACT (Reasoning and Action) model. Agents leverage a variety of Tools, including built-in utilities for command execution, web searching, and code analysis, as well as custom Python functions. The framework supports complex workflows through Handoffs, allowing agents to delegate tasks to specialized agents, and Patterns, which define structured interaction paradigms like Swarm, Hierarchical, or Chain-of-Thought. Observability is provided via OpenTelemetry and Phoenix for detailed tracing, and a Human-In-The-Loop (HITL) module allows for seamless user intervention.

Quick Start & Requirements

• Install: pip install cai-framework
• Prerequisites: Python 3.12, Git. OS X and Ubuntu installations require specific package manager commands. Windows users can utilize WSL.
• Setup: Requires a .env file for LLM API keys (e.g., OpenAI, Anthropic, Ollama).
• Launch: cai
• Docs: https://github.com/aliasrobotics/cai

Highlighted Details

• Supports over 300 LLMs via LiteLLM, including models from OpenAI, Anthropic, and Ollama.
• Features an agentic Pattern system for defining agent coordination and task delegation.
• Integrates with external tools and services via the Model Context Protocol (MCP).
• Includes comprehensive AI observability with OpenTelemetry tracing.

Maintenance & Community

• Active development with contributions encouraged via pre-commit hooks.
• Discord community available: https://discord.gg/fnUFcTaQAC
• Project is co-funded by the European EIC accelerator project RIS.

Licensing & Compatibility

• Open source, free for research purposes. Commercial or professional use requires a license.

Limitations & Caveats

• The framework is in active development and may not work flawlessly.
• Users are responsible for ensuring their use complies with applicable laws and ethical guidelines; the authors do not promote unauthorized system tampering.