bug-reaper: Web2 bug bounty Agent Skill — evidence-based, no AI slop

by shaniidev · Agent Tool · ★ 71

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install bug-reaper

git clone https://github.com/shaniidev/bug-reaper .cursor/skills/bug-reaper     # Cursor
git clone https://github.com/shaniidev/bug-reaper .claude/skills/bug-reaper     # Claude Code

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 66/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars71
Forks10
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score66/100
Open Issues1
Last Updated2026-02-21
Created2026-02-21
Platformsbrowser, python
Est. Tokens~9k

About bug-reaper

BugReaper Structured web2 bug bounty AI skill — 18 vulnerability classes, 4 bug bounty platforms, zero AI slop. Compatible with OpenClaw, Cursor, Claude Code, Antigravity, and Windsurf. BugReaper is an Agent Skill that turns any compatible AI agent into a disciplined web2 bug bounty hunter. It enforces evidence-ba

Compatible Skills

These tools work well together with bug-reaper for enhanced workflows:

  • communitytools — semantic(0.20)+complementary+shared_fw(anthropic)+same_lang+similar_pop+shared_platform (65%)
  • h1-brain — semantic(0.42)+complementary+same_lang+similar_pop+shared_platform (65%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

View on GitHub → Browse Agent Tool tools