New BugHunter Toolkit Uses AI to Automate Bug Bounty Hunting

Key Takeaways

• A new open-source toolkit, BugHunter, automates the entire bug bounty hunting process.
• Initially leveraging Anthropic’s Claude Code, BugHunter now supports free and low-cost AI providers like Ollama and Groq.
• The platform covers reconnaissance, multi-class vulnerability testing for Web2 and Web3, finding validation, and report generation for major bug bounty platforms.
• It includes advanced features such as cross-session memory persistence and specialized AI agents for various tasks.

AI-Driven Automation Arrives for Bug Bounty Hunters with BugHunter Toolkit

The cybersecurity research community is closely examining BugHunter, an innovative open-source toolkit engineered to streamline and automate the entire bug bounty hunting lifecycle. Developed by security researcher Shuvon Md Shariar Shanaz and hosted on GitHub, this platform, which began its journey powered by Anthropic’s Claude Code, has significantly expanded its reach by integrating support for a range of free and economical AI providers, including Ollama and Groq.

BugHunter’s ambition is to provide a comprehensive solution for vulnerability discovery and reporting, all accessible via a single terminal command. Its capabilities span every critical stage of a bug bounty engagement: from initial subdomain enumeration and live host discovery to extensive vulnerability testing across more than 20 Web2 and 10 Web3 bug categories. The toolkit also incorporates a “7-Question Gate” for finding validation and generates submission-ready reports tailored for leading platforms such as HackerOne, Bugcrowd, Intigriti, and Immunefi.

Enhanced Accessibility Through Standalone CLI and Diverse AI Support

What began as a tool primarily accessible to users with Claude Code or Claude Pro subscriptions has evolved into a fully standalone command-line interface (CLI) tool. The bughunter command, now operational with a variety of free and low-cost AI providers, dramatically reduces the entry barrier for independent security researchers. This strategic shift makes advanced bug bounty automation more widely available. Supported free and low-cost providers include:

• Ollama: Offers completely offline operation, running directly on the researcher’s local machine at no monetary cost.
• Groq: Provides a free cloud tier known for its exceptionally fast inference speeds.
• DeepSeek: A cloud-based option priced at approximately $0.001 per 1,000 tokens.
• Claude API / OpenAI: Paid options retained for users who prefer leveraging Anthropic or OpenAI’s advanced models.

BugHunter intelligently prioritizes AI providers, defaulting to the most cost-efficient option available (Ollama → Groq → DeepSeek → Claude → OpenAI). Researchers retain full control, with the ability to switch providers at any time using the bughunter setup command.

A Structured Workflow for Professional Bug Hunting

Upon installation, the toolkit presents a well-structured CLI that closely mirrors a professional bug bounty workflow, guiding researchers through each phase:

bughunter recon target.com      # Attack surface mapping
bughunter hunt  target.com      # Multi-class vulnerability testing
bughunter validate "finding"    # 7-Question Gate validation
bughunter report                # Generates platform-specific submission
bughunter chat                  # Interactive AI hunting shell

The integral “7-Question Gate,” activated during the validate command, serves as a crucial filter, designed to identify and eliminate weak or duplicate findings before a researcher invests time in a potentially fruitless submission. Under the hood, BugHunter orchestrates approximately 35 scanning tools, including industry staples such as subfinder, httpx, nuclei, katana, ffuf, and dalfox. The toolkit is engineered to gracefully skip any missing tools without generating hard errors, ensuring operational continuity.

Advanced Features: Memory Persistence and Web3 Auditing

One particularly notable technical innovation is BugHunter’s cross-session memory persistence. The toolkit logs discovered findings and vulnerability patterns into a JSONL-based memory store. This allows patterns identified on one target to be leveraged as contextual information when testing new targets, enhancing the efficiency and intelligence of subsequent hunts. Session state is also preserved across restarts, enabling researchers to resume interrupted hunts and prioritize untested endpoints using bughunter pickup target.com.

Beyond conventional web application testing, BugHunter includes a dedicated smart contract audit mode. This specialized module covers 10 critical Web3 vulnerability classes, encompassing threats like reentrancy, flash loan attacks, oracle manipulation, and proxy/upgrade flaws. An integrated token auditor module further scans for indicators of rug pulls, mint authority, LP lock status, honeypot detection, and bonding curve anomalies—features highly relevant for Immunefi-style Web3 bounty programs.

Specialized AI Agents and Versatile Deployment

The toolkit’s sophisticated architecture is powered by nine specialized AI agents, each tasked with handling specific elements of the bug bounty pipeline. These include a recon agent, report writer, validator, Web3 auditor, chain builder, autopilot, recon ranker, token auditor, and a credential hunter. The credential hunter agent is notable for incorporating built-in legal guardrails that prevent any credential spraying activity, adhering to ethical hacking principles.

BugHunter offers flexible installation options, deployable as a Claude Code plugin, a standalone CLI, or integrated into alternative agent harnesses such as OpenCode, Pi Agent, and Codex. This versatility positions it as one of the most adaptable open-source offerings for AI-assisted bug bounty automation currently available on GitHub.

What You Should Do

For security researchers and organizations interested in leveraging AI for bug bounty hunting:

• Explore BugHunter’s Capabilities: Review the GitHub repository to understand its features and how it can integrate into your existing workflow.
• Consider Ethical Implications: When using automated tools, ensure compliance with program rules and ethical guidelines for bug bounty hunting.
• Start with Free AI Providers: Utilize the free tiers of Ollama or Groq to experiment with the toolkit at no cost.
• Contribute to Open Source: If you identify areas for improvement or new features, consider contributing to the project to enhance its capabilities for the community.

Disclaimer: HackersRadar reports on cybersecurity threats and incidents for informational and awareness purposes only. We do not engage in hacking activities, data exfiltration, or the hosting or distribution of stolen or leaked information. All content is based on publicly available sources.