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reverse-engineering逆向工程

Agent Skill

reverse-engineering 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

245

周安装

10

GitHub Stars

公开资料未说明

下载量

79
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:reverse-engineering(逆向工程)
来源仓库:https://github.com/r00tedbrain-backup/skills
仓库路径:skills/reverse-engineering
安装命令:
npx skills add https://github.com/r00tedbrain-backup/skills --skill reverse-engineering
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/r00tedbrain-backup/skills --skill reverse-engineering

简介

reverse-engineering 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词快速定位候选结果时使用。

  • 适用于研究检索类任务,可结合来源仓库和原始 README 核验具体用法。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限范围和操作边界。
  • 安装前建议核实维护状态,避免触发联网或文件读写等敏感操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Reverse Engineering & Debugging

Professional methodology for static analysis, dynamic analysis, debugging, and binary exploitation.

Quick Reference — Load the Right Reference File

TaskReference File
Static analysis, disassembly, Ghidra, radare2, objdump, patchingreferences/static-analysis.md
GDB (+ pwndbg/gef/peda), LLDB, strace/ltrace, crash analysisreferences/dynamic-debugging.md
Android APK, DEX, smali, ADB, Frida on Android, repackagingreferences/android-re.md
iOS IPA, Mach-O, class-dump, Frida ObjC/Swift, Keychainreferences/ios-re.md
macOS XPC, launchd, kext, SIP, Linux kernel modulesreferences/macos-kernel-re.md
Windows PE, WinDbg, x64dbg,.NET/dnSpy, kernel driversreferences/windows-re.md
Frida scripting, hooking Java/Native/ObjC, SSL unpin, gadgetreferences/frida.md
.NET IL, dnSpy, de4dot, Java/JVM, Kotlin, Unity/IL2CPP, Monoreferences/managed-code-re.md
Malware, obfuscation, packer analysis, IOC extraction, Volatilityreferences/malware-analysis.md
CTF pwn/rev, BOF, ROP, heap exploitation, pwntools, angr/Z3references/exploit-dev.md
Network protocol RE, Wireshark, mitmproxy, Protobuf, gRPC, Lua dissectors, Boofuzzreferences/protocol-re.md
Firmware, binwalk, QEMU emulation, JTAG/UART, U-Boot, IoTreferences/firmware-embedded.md
EAC, BattlEye, Vanguard, FACEIT, VAC, kernel AC analysisreferences/anticheat-re.md
Ghidra Python/Java scripts, headless, vulnerability finding, custom analyzersreferences/ghidra-scripting.md
IDAPython / IDALib scripts, Hex-Rays API, batch decompile, OLLVM helpersreferences/idapython.md
Unicorn engine emulation, function-level emulation, JNI stubbing, syscall simreferences/unicorn-emulation.md
Stripped symbol recovery, magic numbers, paired calls, xref analysisreferences/symbol-recovery.md
C/C++ structure recovery, vtables, std::string/vector/map, field type inferencereferences/struct-recovery.md

Bundled Tools (tools/)

The skill ships ready-to-use companion utilities (all original work, MIT-licensed):

ToolPurpose
tools/ida_export_plugin.pyIDA Pro plugin (Ctrl-Shift-E) — exports the IDB into a decompile/ directory of plain-text files an agent can read directly
tools/dex_memory_dumper.jsFrida agent — dumps DEX from a running Android process via memory scan + ClassLoader traversal
tools/mcp/Setup notes and config snippets for connecting agents to upstream MCP servers (ida-pro-mcp, GhidraMCP, r2mcp)

See tools/README.md for usage details. The tools/mcp/ directory documents the live-query workflow (alternative to file export) — both modes are supported by the methodology files above.


Universal First Steps

Before loading any reference file, establish context:

1. Identify the Target

file <binary>           # file type, arch, bits, stripped?
xxd <binary> | head -4  # magic bytes
strings -a <binary> | head -60
checksec --file=<binary>  # NX, PIE, RELRO, stack canary, ASLR

Binary format decision tree:

  • ELF → Linux native → references/static-analysis.md + references/dynamic-debugging.md
  • PE/PE32+ → Windows native → references/windows-re.md + references/static-analysis.md
  • PE with.NET metadata → references/managed-code-re.md (dnSpy first)
  • Mach-O → macOS/iOS → references/macos-kernel-re.md + references/ios-re.md
  • DEX/APK/AAB → Android → references/android-re.md
  • JAR/WAR/AAR → Java → references/managed-code-re.md
  • .sys driver → references/windows-re.md (kernel section) or references/anticheat-re.md
  • Assembly-CSharp.dll → Unity → references/managed-code-re.md (Unity section)
  • Unknown/firmware → references/firmware-embedded.md (binwalk + entropy)

Task-type decision tree (applies to any format):

  • Stripped binary, unknown functions → references/symbol-recovery.md
  • Unknown struct layouts in decompilation → references/struct-recovery.md
  • Need to run just one function in isolation → references/unicorn-emulation.md
  • Using IDA Pro for analysis → references/idapython.md
  • Using Ghidra for analysis → references/ghidra-scripting.md

2. Establish Scope

Ask the user (or infer from context):

  • Goal: understand logic / find vuln / bypass protection / patch / CTF flag / malware IOCs?
  • Platform: Linux / Windows / macOS / Android / iOS / embedded?
  • Tools available: Ghidra / IDA / radare2 / Binary Ninja / Hopper?
  • Dynamic possible?: Can we run it? VM? Emulator? Physical device?

3. Choose Analysis Mode

Static only  → No execution risk, slower understanding
Dynamic only → Fast but misses dead code
Static + Dynamic (recommended) → Static for map, dynamic for runtime truth

Core Toolchain Summary

Static

ToolBest For
GhidraFull decompilation, scripting, free
radare2 / cutterCLI powerhouse, scripting, embedded
Binary NinjaAPI-first, fast, commercial
IDA Pro / IDA FreeIndustry standard, best signatures
objdumpQuick disassembly, no install
readelf / nmELF symbol/section inspection
jadxAndroid DEX → Java, GUI
apktoolAPK unpack / repack / smali

Dynamic

ToolBest For
GDB + pwndbg/peda/gefLinux ELF debugging
LLDBmacOS/iOS/Swift debugging
FridaCross-platform hooking, no source
strace / ltraceSyscall / library call tracing
ValgrindMemory errors, Helgrind
WinDbgWindows kernel + user mode
x64dbgWindows GUI debugger

Network

ToolBest For
Wireshark / tsharkPacket capture + dissection
mitmproxy / Burp SuiteHTTP/S MITM
FridaIn-process SSL unpin
tcpdumpHeadless capture

Methodology Frameworks

Static Analysis Workflow

1. file + strings + checksec           → quick triage
2. Entropy analysis                    → packed/encrypted?
3. Import table / symbol table         → understand capabilities
4. Load in decompiler                  → rename, retype, annotate
5. Identify key functions              → main(), crypto, network, anti-debug
6. Trace data flow                     → user input → sink
7. Document findings                   → comment inline

Dynamic Analysis Workflow

1. Set up isolated environment         → VM / container / device
2. Run with strace/ltrace first        → understand syscall footprint
3. Attach debugger                     → set breakpoints at key functions
4. Observe runtime behavior            → memory, registers, branches taken
5. Correlate with static              → validate decompiler output
6. Patch / hook as needed             → bypass checks, log values

Vulnerability Discovery Workflow

1. Attack surface mapping             → inputs: file, network, env vars, args
2. Dangerous function search          → strcpy, gets, sprintf, memcpy, system
3. Integer overflow candidates        → size calculations, loops
4. Format string candidates           → printf(user_input)
5. UAF / double-free candidates       → heap allocation patterns
6. Trigger + confirm                  → crash → controlled → exploitable

Anti-Analysis Bypass — Quick Reference

Anti-Debug Detection

# Check if binary detects debugger
strings <bin> | grep -iE "ptrace|debugger|isDebuggerPresent|TracerPid"

# Linux: ptrace self-detection
# Bypass: preload hook or patch the ptrace call

Common Protections

ProtectionDetectionBypass
ptrace anti-debugstrace shows ptrace(TRACEME)Patch JNZ→JMP or LD_PRELOAD fake ptrace
Timing checksrdtsc / clock_gettime in loopPatch comparison or NOP
Checksum/integrityHash of own.text sectionPatch after decryption, before check
Packer (UPX etc.)High entropy + small importsupx -d / dump from memory after unpack
Obfuscated stringsNo readable stringsRun + extract from memory / Frida hook
SSL pinning (mobile)Network fail in appFrida ssl-unpin / see references/frida.md

Output Standards

When reporting RE findings, always structure output as:

## Binary: <name>
- **Format**: ELF64 / PE32+ / DEX / Mach-O
- **Arch**: x86_64 / ARM64 / ARMv7 / MIPS
- **Stripped**: Yes/No | **PIE**: Yes/No | **NX**: Yes/No

## Key Findings
1. <function name @ offset> — <what it does>
2. ...

## Vulnerability / Behavior
- <description with evidence>
- Offset: 0x<addr>
- Triggerable via: <input vector>

## Recommended Next Steps
- [ ] <action>

Naming Conventions for Decompiler Work

Follow these standards when annotating in Ghidra / IDA / r2:

Functions:  verb_noun_context      → decrypt_config_xor, check_license_hwid
Variables:  type_purpose           → buf_user_input, sz_packet, ptr_heap_chunk
Structs:    ST_<name>              → ST_PacketHeader, ST_LicenseData
Labels:     loc_<purpose>         → loc_anti_debug_fail, loc_success

Scripting Quick Starters

See references/frida.md for full Frida patterns.

GDB Python one-liner (log function args)

# In GDB: source this file
import gdb
class LogArgs(gdb.Breakpoint):
    def stop(self):
        frame = gdb.selected_frame()
        print(f"[*] {frame.name()} rdi={gdb.parse_and_eval('$rdi')} rsi={gdb.parse_and_eval('$rsi')}")
        return False  # don't stop, just log
LogArgs("target_function")

radare2 batch analysis

r2 -A -q -c "afl~suspicious; pdf @ sym.check_license" <binary>

Ghidra headless analysis

$GHIDRA_HOME/support/analyzeHeadless /tmp/proj MyProject \
  -import <binary> -postScript PrintAST.java -scriptPath ~/ghidra_scripts

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.56%
按下载量换算27

Claude

31.6%
按下载量换算25

Cursor

16.73%
按下载量换算13

Gemini CLI

8.64%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

未通过

Snyk

可疑

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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