I Turned Claude into an Autonomous Bug Bounty Hunter with 124 Skills, 3 Hooks, and a Kali Container

2026-07-26 · Source: AI on Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cybersecurity & Data Privacy, Software Development & Engineering · Depth: Advanced, medium

Summary

Rohan Badekan developed Aii-Aii Hunter, an autonomous bug bounty hunting framework built on Claude Code, designed to automate the orchestration of offensive security tasks. This system integrates 124 skills, 3 hooks, and utilizes a Kali Linux container to execute 110 pentest tools. Aii-Aii Hunter addresses the common bottleneck of knowing what to run and when, by codifying 35,545 lines of hunting methodology into skills covering 37 vulnerability classes, 7 platform-specific areas, 11 enterprise/infra, and 4 AI/LLM categories. Its architecture includes auto-routing prompts via 102 regex patterns, enforcing scope with a PreToolUse hook, and logging tool usage. The framework also features a 7-Question Gate for rigorous finding validation and a static analysis layer for high-confidence bug detection.

Key takeaway

For bug bounty hunters or AI Security Engineers aiming to scale their operations, consider building an autonomous framework like Aii-Aii Hunter. You should codify your hunting methodologies into AI-loadable skills and integrate tool execution via a containerized environment. Prioritize implementing robust guardrails, especially scope enforcement and a multi-question validation gate, to significantly reduce false positives and ensure high-quality, in-scope findings, allowing you to focus on complex logic bugs.

Key insights

AI-assisted hacking excels by orchestrating codified methodology, tool execution, and robust guardrails, not just basic chatbot queries.

Principles

• Codify methodology for AI-driven security.
• AI must execute tools, not just advise.
• Implement guardrails for scope and validation.

Method

Build skills from disclosed reports, implement hooks for auto-routing and scope enforcement, bridge pentest tools via MCP, and integrate a multi-stage engagement flow with validation gates.

In practice

• Codify top 3 vulnerability classes as skills.
• Implement an auto-routing hook for prompts.
• Bridge pentest tools via MCP for AI execution.

Topics

• Bug Bounty Hunting
• AI Orchestration
• Offensive Security
• Pentest Automation
• Claude Code
• Model Context Protocol

Best for: AI Engineer, AI Security Engineer, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI on Medium.