No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by dslsdzc · Agent Tool · ★ 59
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is rev-skills safe to install? View the security audit →
rev-skills — 通用逆向工程 AI 技能库 English | 中文 122 个逆向工程技能，覆盖恶意软件分析、软件逆向、固件/嵌入式、协议逆向、移动应用、脱壳/反混淆、软件破解、漏洞挖掘、托管代码、取证/情报、CTF。通用、可发布：不假设用户已装任何工具，每个技能自带跨 OS 安装指引。 使用边界：本技能库仅用于安全研究与授权范围内的分析。使用前须取得目标方授权；禁止用于未经授权的逆向、破解、绕过验证或恶意软件活动。逆向工程的合法性因司法辖区而异（如美国 DMCA 反规避条款、各地软件保护条例），使用者须自行遵守所在地法律，并自行承担违规使用的一切责任。本库内容为通用方法论，不针对任何具体目标。 安装（三种方式） 方式一：npx（推荐，支持 7 种 AI 工具） 方式一自建安装器额外处理 Cursor / Copilot / Windsurf 的规则聚合（.mdc / 说明文件），这是标准 skills CLI 没有的能力；只装 Claude Code 系可用方式二。 方式二：标准 skills CLI（agentskills.io 兼容） 本库遵循 Agent Skills 规范，可被任意兼容运行时（Claude Code / Codex / Cursor / Gemini CLI 等 50+ 工具）直接发现与安装： bash npx skills add dslsdzc/rev-skills # 项目作用域（.claude/skills/） npx skills add dslsdzc/rev-skills -g # 全局（/.claude/skills/） npx skills add dslsdzc/rev-skills -l # 先列出技能，
| Stars | 59 |
| Forks | 8 |
| Language | JavaScript |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 64.0754768472548/100 |
| Last Updated | 2026-09-15 |
| Created | 2026-08-17 |
| Platforms | claude-code, node |
| Est. Tokens | ~14k |
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rev-skills is 122 个逆向工程 AI 技能（可发布、跨平台）：恶意软件分析 / 软件逆向 / 固件嵌入式 / 协议逆向 / 移动应用 / 脱壳反混淆 / 软件破解 / 漏洞挖掘 / 托管代码 / 取证情报 / CTF。. It is categorized as a Agent Tool with 59 GitHub stars.
rev-skills is primarily written in JavaScript. It covers topics such as ai-agents, claude-code, ctf.
You can find installation instructions and usage details in the rev-skills GitHub repository at github.com/dslsdzc/rev-skills. The project has 59 stars and 8 forks, indicating an active community.
rev-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 rev-skills on Agent Skills Hub include pentest-skills, node9-proxy, SecOpsAgentKit. 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: