ipsw-skill: A SKILL.md for ipsw

by blacktop · Claude Skill · ★ 89

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

How to install ipsw-skill

npx skills add https://github.com/blacktop/ipsw-skill --skill ipsw
git clone https://github.com/blacktop/ipsw-skill /tmp/ipsw-skill

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 71/100

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.

appleclaude-codeclaude-skillscodexipswreverse-engineeringskillvulnerability-research

Quick Facts

Stars89
Forks12
LanguageShell
CategoryClaude Skill
LicenseMIT
Quality Score71/100
Last Updated2026-09-27
Created2025-12-24
Platformsclaude-code, cli, codex
Est. Tokens~6k

About ipsw-skill

ipsw-skill An AI agent skill for Apple firmware and binary reverse engineering using the ipsw CLI tool. Supports Claude Code, Codex CLI, Gemini CLI, and Pi (pi-coding-agent). What This Skill Provides This skill empowers AI agents to assist with: Downloading/extracting firmware - IPSWs, OTAs, kernelcaches, dyldsharedcache Userspace reverse engineering - DSC disassembly, symbol lookup, xrefs,...

Compatible Skills

These tools work well together with ipsw-skill for enhanced workflows:

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  • vowline — semantic(0.39)+complementary+similar_pop+shared_platform (49%)
  • ui-craft — semantic(0.24)+complementary+similar_pop+shared_platform (48%)

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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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