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 morluto · MCP Server · ★ 334
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-reverse-engineering safe to install? View the security audit →
Awesome Reverse Engineering Featured: REA — Agent-oriented reverse-engineering tools, from application behavior to native binaries. By the creators of awesome-reverse-engineering. A curated starting point for understanding binaries, applications, firmware, file formats, and protocols. Find a tool by the work you need to do. Each entry describes its purpose; commercial tools are marked commercial. This is an initial selection, open to additions and corrections. Start here | Unpack a Python, Go, Unity, Godot, or obfuscated .N
| Stars | 334 |
| Forks | 73 |
| Category | MCP Server |
| License | CC0-1.0 |
| Quality Score | 55.5421429489666/100 |
| Open Issues | 1 |
| Last Updated | 2026-10-13 |
| Created | 2026-10-09 |
| Platforms | mcp |
| Est. Tokens | ~23k |
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awesome-reverse-engineering is Curated reverse-engineering tools and learning resources for binaries, apps, firmware, formats, and protocols.. It is categorized as a MCP Server with 334 GitHub stars.
You can find installation instructions and usage details in the awesome-reverse-engineering GitHub repository at github.com/morluto/awesome-reverse-engineering. The project has 334 stars and 73 forks, indicating an active community.
awesome-reverse-engineering is released under the CC0-1.0 license, making it free to use and modify according to the license terms.
The top alternatives to awesome-reverse-engineering on Agent Skills Hub include reverify, open-reverselab, ghidra-cli. 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: