Claude-Code-CyberSecurity-Skill: 22 production-quality Claude Code Skills for cybersecurity professionals , covering offensive security

by Masriyan · Claude Skill · ★ 490

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

How to install Claude-Code-CyberSecurity-Skill

git clone https://github.com/Masriyan/Claude-Code-CyberSecurity-Skill.git

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

Security audit verdict: SAFE · quality 69/100

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.

claude-skillsclaudecode

Quick Facts

Stars490
Forks93
LanguagePython
CategoryClaude Skill
Quality Score69/100
Open Issues1
Last Updated2026-10-20
Created2026-02-27
Platformsclaude-code, python
Est. Tokens~16k

About Claude-Code-CyberSecurity-Skill

Claude Code CyberSecurity Skill Collection 15 production-quality Claude Code Skills for cybersecurity professionals — covering offensive security, defensive operations, reverse engineering, threat hunting, CSOC automation, and more. Version 2.0 — rebuilt from the ground up for Claude Code. Transform Claude Code into your ultimate cybersecurity co-pilot.

Compatible Skills

These tools work well together with Claude-Code-CyberSecurity-Skill for enhanced workflows:

  • falcon-mcp — semantic(0.32)+complementary+same_lang+similar_pop+shared_platform (61%)
  • revula — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (60%)
  • Reversecore_MCP — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (58%)
  • binary-ninja-headless-mcp — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)

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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:

View on GitHub → Browse Claude Skill tools