awesome-reverse-engineer-anything: Awesome REA: what AI agents reverse-engineered and rebuilt, and which ones really used REA

by AIshihzong · MCP Server · ★ 507

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

Security audit verdict: SAFE · quality 55/100

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. Full audit →

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.

ai-agentsai-reverse-engineeringawesomeawesome-listcase-studiesclaude-codeclean-roomcodexdecompilationdecompiler

Quick Facts

Stars507
Forks134
LanguagePython
CategoryMCP Server
LicenseCC0-1.0
Quality Score55/100
Open Issues3
Last Updated2026-11-06
Created2026-10-13
Platformsclaude-code, codex, mcp, python
Est. Tokens~21k

About awesome-reverse-engineer-anything

Awesome REA: Reverse Engineer Anything with AI English · 简体中文 What AI agents reverse-engineered and rebuilt, and which ones really used REA. Unofficial. Not affiliated with morluto/rea. Find a project by the app it replaces · Did it really use REA? · Does REA help? The evidence · New this week · Submit a case "REA" started as morluto/rea (Reverse Engineer Anything, 380k+ stars as of 2026-10-25),...

Compatible Skills

These tools work well together with awesome-reverse-engineer-anything for enhanced workflows:

  • ai-reverse-engineering — semantic(0.54)+complementary+rare_topics+same_lang+similar_pop+shared_platform (73%)
  • Awesome-REA — semantic(0.63)+rare_topics+same_lang+similar_pop+shared_platform (71%)

awesome-reverse-engineer-anything alternative? Top 6 similar tools

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    What The Function: your AI agent decompiles games you own into C that compiles to the exact same bytes. Runs l

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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:

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