Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by crazyMarky · Codex Skill · ★ 277
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is pentest-skills safe to install? View the security audit →
Pentest-Skills 专为 AI CLI 工具（Claude Code / Gemini CLI）设计的模块化渗透测试技能集合。 English | 简体中文 项目概述 💡 核心理念 告别复杂的命令行，用自然语言完成专业渗透测试。 你只需描述测试目标，Claude Code 会自动选择合适的工具、执行命令、分析结果。 Pentest-Skills 为渗透测试工作流程提供原子级能力。每个技能包含： 知识文档 - 命令模板和工具使用指南 辅助脚本 - Python/Bash 自动化脚本 参考文档 - 全面的工具文档 资源文件 - 字典、载荷和资源 快速开始 1️⃣ 安装 Claude Code 在使用本项目的技能之前，你需要先安装 Claude Code 或其他 AI Coding 工具。 使用官方脚本安装 安装完成后,验证一下: 如果显示版本号，说明安装成功! Claude Code 官方安装教程： https://code.anthropic.com/docs Claude Code菜鸟安装入门教程： https://www.runoob.com/claude-code/claude-code-install.html Skills入门教程： https://www.runoob.com/claude-code/claude-agent-skills.html 2️⃣ 安装技能 将技能复制到你的 目录： 重启你的 IDE 以加载技能。 3️⃣ 开始测试 打开 Claude Code，用自然语言描述你的测试需求： 简单的自然语言描述，即可触发skills中的端口扫描技能，扫描结果会自动分析服务版本。 就这么简单！
| Stars | 277 |
| Forks | 29 |
| Language | Python |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 64.5783016694011/100 |
| Open Issues | 2 |
| Last Updated | 2026-06-04 |
| Created | 2026-02-06 |
| Platforms | claude-code, cli, codex, gemini, python |
| Est. Tokens | ~302k |
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pentest-skills is 💬 🚀 告别繁琐命令行，用自然语言驱动专业级渗透测试。 ⚡ 让安全测试从未如此简单、高效。Forget complex command lines. 🛡️ Professional penetration testing, powered by natural language.. It is categorized as a Codex Skill with 277 GitHub stars.
pentest-skills is primarily written in Python. It covers topics such as ai-agents, claude-code, codex-cli.
You can find installation instructions and usage details in the pentest-skills GitHub repository at github.com/crazyMarky/pentest-skills. The project has 277 stars and 29 forks, indicating an active community.
pentest-skills is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to pentest-skills on Agent Skills Hub include cccc, quint-code, claude-codex-settings. 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: