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AI Agent Analysis
RS

zhaoxuya520/reverse-skill

Reverse Engineering / Authorized Penetration Testing / Security Research Skill Router Pack AI-powered routing + On-demand toolchain bootstrapping + Self-evolving knowledge base Supports Claude Code, Kiro, Cursor, Cline, and other AI coding clients 逆向/渗透/安全技能路由包 - AI 自动路由 + 按需自举工具链 + 自动进化经验库 | 支持 Claude Code / Kiro / Cursor / Cline 等代码 AI 客户端

stars
25k
Language
PowerShell
GitHub
Source and compliance noteLast synced: Aug 16, 2026

Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.

Original GitHub sourceMethodologyEditorial Policy

Overview

reverse-skill is a cybersecurity skills router pack that equips AI coding agents (Claude Code, Kiro, Cursor, Cline, etc.) with structured, scenario-based playbooks for reverse engineering, authorized penetration testing, and security research. It provides AI-driven routing to the correct methodology and toolchain (jadx, Frida, IDA, BurpSuite, etc.), on-demand toolchain bootstrapping, and a self-evolving knowledge base to reuse experience across tasks.

Installation

git clone https://github.com/zhaoxuya520/reverse-skill.git, then run the platform-specific tool index refresh script (e.g., bash skills/scripts/refresh-tool-index.sh on Linux/macOS, powershell -File skills/scripts/refresh-tool-index.ps1 on Windows).

Problem solved

AI agents often lack domain knowledge about which reverse engineering or pentesting tool to use for a given task, leading to guesswork and repeated mistakes. This framework solves that by providing a structured routing system that maps task types (APK, ELF, JS, PCAP, CTF) to proven playbooks, automatically checks available tools, and bootstraps missing toolchains on demand. It also captures and reuses experience through a self-evolving knowledge base, preventing the same errors from recurring.

What you can build

Developers can build AI-assisted security analysis workflows that handle APK/Android reverse engineering, iOS/mobile analysis, frontend JS encryption cracking, binary analysis (ELF/PE), PCAP analysis, and CTF challenges. The ceiling is high: with the routing and toolchain bootstrapping, an AI agent can autonomously execute complex multi-step security assessments, generate evidence-based reports, and maintain a field journal of findings. Real-world use cases include automated malware analysis, vulnerability research, authorized penetration testing, and security education.

Community sentiment

Positive

No community feedback yet.

Concerns

No concerns documented yet.

Bottom line

This framework is ideal for security professionals, ethical hackers, and researchers who use AI coding agents and need structured, repeatable workflows for reverse engineering and authorized pentesting. It should be avoided by those without proper authorization or ethical boundaries, as the automation could be misused. The key trade-off is between efficiency and control: while it greatly accelerates security analysis, it requires responsible use and human oversight to ensure actions remain legal and ethical.

Analyzed by Git-Stars - 8/1/2026