Seep-Reverse-Lab: Agent-Native multi-platform reverse engineering and CWE-602 client-side authorization audit workbench

by angusdevgo · Agent Tool · ★ 1.4k

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

Security audit verdict: SAFE · quality 58/100

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.

Quick Facts

Stars1,375
Forks391
LanguageLua
CategoryAgent Tool
LicenseGPL-3.0
Quality Score58/100
Last Updated2026-10-12
Created2026-09-23
Platformscli
Est. Tokens~22k

About Seep-Reverse-Lab

Seep Reverse Lab Agent-Native · Multi-Platform Reverse Engineering · CWE-602 Authorization Audit · Autonomous Security Workbench <img src="https://i

Compatible Skills

These tools work well together with Seep-Reverse-Lab for enhanced workflows:

  • cheatengine-mcp-bridge — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (58%)
  • android-reverse-engineering-skill — semantic(0.26)+complementary+similar_pop+shared_platform (49%)
  • re-skill — semantic(0.22)+complementary+similar_pop+shared_platform (48%)
  • ablation — semantic(0.35)+complementary+similar_pop (47%)
  • bn — semantic(0.20)+complementary+similar_pop+shared_platform (47%)

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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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