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Claude Code Reverse

Community
majiayu000
claude-code-reverse

对用户拥有或明确获授权的本机可执行文件、应用二进制和版本产物做只读静态逆向,包括 Claude Code 及其他 CLI、Mach-O、ELF、PE、Wasm 或打包应用。仅在用户明确要求“逆向、扒实现、查二进制字符串/符号/依赖、验证内部行为、比较两个版本”时使用;不要因普通提及软件而触发,也不要用于执行未知样本、绕过授权/计费、破解或再分发。

Overview

Publishermajiayu000
Repositoryspellbook
Skill nameclaude-code-reverse
Stars
280
Forks
26
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by majiayu000 on GitHub. Read the source before you install it.

Installation

Install the Claude Code Reverse AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/majiayu000/spellbook.git /tmp/spellbook
mkdir -p .claude/skills
cp -r /tmp/spellbook/skills/claude-code-reverse .claude/skills/claude-code-reverse
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Claude Code Reverse in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Claude Code Reverse on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Claude Code Reverse is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Local Binary Reverse

对明确指定的本机目标做证据优先的静态分析。默认只读,不执行目标,也不把“可见字符串”夸大为“已证明运行时行为”。

自主边界

  • 可直接执行:读取用户指定的单个本机文件;运行 file、哈希、strings、符号表、依赖表、段表和只读反汇编工具;把分析缓存写入当前用户的私有 cache。
  • 先征得同意:运行目标、附加调试器、注入/hook、解包到用户目录、安装分析工具、上传样本、分析未获授权的软件或受保护数据。
  • 直接拒绝:绕过许可证、计费或访问控制,提取凭据,制作破解补丁,规避检测,或再分发专有代码/资源。
  • 不确定所有权、目标路径或交付问题时先澄清,不要扫描整台机器寻找“可能的目标”。

1. 锁定目标与问题

先记录:

  1. 精确目标路径或命令名。
  2. 用户要验证的具体问题,例如 UI 文案来源、功能开关、网络端点、依赖或版本差异。
  3. 对比版本的两个精确文件(如适用)。

不要把进程名、应用名或猜测路径当成已确认目标。不要运行目标来“看看会发生什么”。

2. 建立文件身份

使用同目录的 extract.sh。它只接受普通文件或可由 command -v 解析的命令,缓存按内容 SHA-256 隔离并存放在 ${XDG_CACHE_HOME:-$HOME/.cache}/claude-code-reverse/

bash
SKILL_DIR=/path/to/claude-code-reverse
bash "$SKILL_DIR/extract.sh" info --target /absolute/path/to/target
bash "$SKILL_DIR/extract.sh" dump --target /absolute/path/to/target
bash "$SKILL_DIR/extract.sh" search --target /absolute/path/to/target "literal anchor"
bash "$SKILL_DIR/extract.sh" diff --target-a /path/to/v1 --target-b /path/to/v2 "literal anchor"

info 必须先给出规范化路径、文件类型、字节数和 SHA-256。若目标在分析期间发生变化,重新执行 infodump;不要复用旧缓存作结论。

3. 按格式选择只读工具

先用 command -v <tool> 验证工具存在。缺失时报告缺失项,不要悄悄换成会执行目标的方案。

格式首选证据可选深入工具
Mach-Ofileotool -Lotool -lnmotool -tvV、已安装的反编译器
ELFfilereadelf -h -l -d -sobjdump -xobjdump -d、已安装的反编译器
PE/COFFfileobjdump -x、ASCII/UTF 字符串objdump -d、已安装的 PE 工具
Wasmfilewasm-objdump -xwasm2wat
ZIP/JAR/APK/打包资源先列目录,不落盘解包在用户批准的临时目录中解包后逐件分析

不要对不可信目标使用 ldd,因为某些实现可能通过加载器执行代码。不要对大文件直接输出完整反汇编、完整字符串或完整符号表;先用字面锚点缩小范围,把原始大输出留在 cache 或单独 artifact 中。

常见失败信号

  • strings 几乎没有输出:目标可能被剥离、压缩、加密或只是启动器;先检查文件类型和段表,不要据此断言“没有实现”。
  • 刚 dump 后却提示 cache 不存在:内容哈希已经变化,说明目标文件被更新;重新执行 infodump,不要复用旧版本结论。
  • 同一字符串重复出现:universal/fat binary 可能包含多个架构切片;先按架构检查,不能把重复次数直接解释为调用次数。
  • ASCII 搜索无命中:PE 或资源文件可能使用 UTF-16;确认本机 strings 实现支持相应编码选项后再查,不要假定跨平台参数一致。

4. 从证据到结论

按以下顺序收敛:

  1. 用产品文案、端点、配置键、错误消息或符号名做字面锚点。
  2. 截取锚点附近上下文,并记录来源文件和 SHA-256。
  3. 交叉检查符号、导入依赖、相邻常量或两个版本的差异。
  4. 区分结论等级:已观察(文件中直接存在)、强推断(多项静态证据一致)、未知(需要运行时或服务端证据)。

字符串存在不等于代码路径可达,导入存在不等于功能被调用,客户端文案也不能证明服务端策略。

5. Claude Code 兼容模式

不提供 --target 时,脚本保留原来的 Claude Code 快捷模式:

bash
bash "$SKILL_DIR/extract.sh" dump
bash "$SKILL_DIR/extract.sh" search "usage limit reached"
bash "$SKILL_DIR/extract.sh" diff 2.1.190 2.1.191 "literal anchor"

需要 Claude Code 的安装位置、锚点地图和特有限制时,读取 references/claude-code.md。其他目标不要套用 Claude 专用锚点。

静态分析边界

静态分析通常无法证明服务端下发内容、运行时生成值、加密后数据、动态加载路径、优化掉的逻辑或混淆变量的真实语义。需要越过这些边界时,明确说明缺少的证据和下一步会产生的副作用,再请求许可。

完成标准

  • 报告目标规范化路径、文件类型、字节数和 SHA-256。
  • 列出本次真实运行的命令和关键输出位置。
  • 每项结论附直接证据,并标记 已观察强推断未知
  • 说明未覆盖的静态分析边界。
  • 确认没有执行或修改目标,也没有把样本上传到外部服务。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Claude Code Reverse AI skill do?

对用户拥有或明确获授权的本机可执行文件、应用二进制和版本产物做只读静态逆向,包括 Claude Code 及其他 CLI、Mach-O、ELF、PE、Wasm 或打包应用。仅在用户明确要求“逆向、扒实现、查二进制字符串/符号/依赖、验证内部行为、比较两个版本”时使用;不要因普通提及软件而触发,也不要用于执行未知样本、绕过授权/计费、破解或再分发。

Why use Claude Code Reverse on TypingMind?

Because you install it once and use it with any model. Claude Code Reverse is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Claude Code Reverse in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/majiayu000/spellbook/tree/main/skills/claude-code-reverse. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Claude Code Reverse?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Claude Code Reverse?

As many as you like. As long as a model supports skills, you can use Claude Code Reverse with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Claude Code Reverse AI skill free?

Yes. It is published on GitHub by majiayu000 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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