h4ckologic/bughunter-ai

BugHunter AI is an autonomous security research framework that automates the process of finding vulnerabilities in websites and web applications. Bug bounty programs are arrangements where companies invite independent researchers to probe their software for security holes and pay rewards for legitimate findings. This tool is designed to handle the entire process, reconnaissance, profiling, attack, and reporting, with minimal human input. You type one command (hunt followed by a target URL) and the framework takes over. Under the hood, a state machine tracks ten phases of a hunt, moving from profiling the application through to generating a professional bug bounty report with severity scores. Twenty specialized AI agents run in parallel, each focused on a different type of vulnerability, covering web, API, mobile, cloud, and AI-specific attack surfaces including the OWASP LLM Top 10. Credentials are stored in an encrypted vault rather than in plain text. The framework integrates with Burp Suite, a widely used security testing tool, via an MCP server connection that lets AI agents inspect and interact with intercepted web traffic. The project is built on top of PAI (Personal AI Infrastructure), which provides structured reasoning, cross-session memory so the system learns from past engagements, and notification support for long-running tasks. It is written in TypeScript and uses the Bun runtime. Claude Code, Anthropic's AI coding assistant, powers the core agent orchestration. The full README is longer than what was shown.