No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by awarexone · Agent Tool · ★ 5.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Agentic-Bug-Hunter safe to install? View the security audit →
AI-powered bug bounty hunting — recon to report, in your terminal. What Is This · Trusted By · Free Setup · Quick Start · Commands · What It Finds · AXguard · Support · FAQ <a href="https://github.com/Awar
| Stars | 5,123 |
| Forks | 905 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 69.0543427803691/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-22 |
| Created | 2026-03-08 |
| Platforms | claude-code, python |
| Est. Tokens | ~22k |
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Agentic-Bug-Hunter is AI-powered bug bounty hunting toolkit that works with or without subscription.. It is categorized as a Agent Tool with 5.1k GitHub stars.
Agentic-Bug-Hunter is primarily written in Python. It covers topics such as ai-security, bug-bounty, bugcrowd.
You can find installation instructions and usage details in the Agentic-Bug-Hunter GitHub repository at github.com/awarexone/Agentic-Bug-Hunter. The project has 5.1k stars and 905 forks, indicating an active community.
Agentic-Bug-Hunter is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Agentic-Bug-Hunter on Agent Skills Hub include claude-bug-bounty, Claude-BugHunter, CyberStrike. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: