ghidra-re-skill: Codex Ghidra reverse engineering skill with headless workflows, bug-hunting bundles, and a live bridge

by OwenPawl · Codex Skill · ★ 72

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

Security audit verdict: SAFE · quality 60/100

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

Stars72
Forks9
LanguagePython
CategoryCodex Skill
Quality Score60/100
Open Issues5
Last Updated2026-05-26
Created2026-03-31
Platformscodex, python
Est. Tokens~33k

About ghidra-re-skill

ghidra-re Works with both OpenAI Codex and Anthropic Claude Code — install once, use with either. is a local skill for Ghidra-based reverse engineering on macOS and Windows, with a workflow tuned for Apple Mach-O binaries, dyld-extracted frameworks, multi-target investigation missions, and a live Ghidra bridge for iterative RE sessions. Dual-host by design.

ghidra-re-skill alternative? Top 1 similar tools

Looking for a ghidra-re-skill alternative? If you're comparing ghidra-re-skill with other codex skill tools, these 1 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • theorist by blader · ⭐ 191

    A Codex/Claude skill that maintains per-repo operating theory documents.

More Codex Skill Tools

Explore other popular codex skill tools:

View all Codex Skill tools →

Popular Python Agent Tools

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 Codex Skill tools