Competition Android Hooking logo

Competition Android Hooking

CommunityPopular
zhaoxuya520
competition-android-hooking

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Android APK hooking, Frida tracing, request-signing recovery, SSL pinning bypass, JNI boundary inspection, and app trust-boundary analysis. Use when the user asks to hook an APK, inspect signer logic, trace Java or native boundaries, bypass pinning or root checks, inspect shared prefs or app databases, or replay accepted mobile requests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Overview

Publisherzhaoxuya520
Repositoryreverse-skill
Skill namecompetition-android-hooking
Stars
36.3K
Forks
5K
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

    Published by zhaoxuya520 on GitHub. Read the source before you install it.

Installation

Install the Competition Android Hooking 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/zhaoxuya520/reverse-skill.git /tmp/reverse-skill
mkdir -p .claude/skills
cp -r /tmp/reverse-skill/CTF-Sandbox-Orchestrator/competition-android-hooking .claude/skills/competition-android-hooking
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competition Android Hooking 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 Competition Android Hooking 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 Competition Android Hooking 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.

Competition Android Hooking

Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.

Use this skill when the decisive path runs through an Android app's live trust boundary rather than static strings alone.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

  1. Preserve the original APK, extracted resources, and decompiled output before patching or resigning.
  2. Start with manifest, exported components, deeplinks, native libs, prefs, local DBs, and bundled configs.
  3. Decide the narrowest runtime boundary to hook: signer, crypto helper, JNI bridge, WebView bridge, or request builder.
  4. Correlate static evidence and dynamic traces before claiming a trust edge is understood.
  5. Reproduce the signed request, accepted token, or gated branch from the smallest hook set.

Workflow

1. Static Triage Before Hooks

  • Map package structure, exported activities, services, receivers, providers, and deeplink handlers.
  • Note SSL pinning logic, root checks, feature flags, token storage, shared prefs, SQLite tables, and protobuf or RPC boundaries.
  • Identify whether the sensitive logic sits in Java, Kotlin, JNI, or a bundled WebView.

2. Hook The Narrowest Boundary

  • Prefer hooking request signers, crypto helpers, keystore access, protobuf encode or decode, or JNI marshaling instead of broad UI hooks.
  • Record plaintext inputs, signed strings, headers, nonces, and outputs at the boundary that actually changes trust.
  • If pinning or environment checks block progress, patch or hook only enough to expose the real request path.

3. Replay The Accepted Path

  • Rebuild the smallest sequence that reaches the accepted server-side branch: local state, nonce, request body, signature, and headers.
  • Keep hook logs, captured request shapes, and local storage paths tied to the same account or session state.
  • If the challenge becomes more about transform recovery than Android runtime, switch back to the broader crypto or mobile skill.

Read This Reference

  • Load references/android-hooking.md for hook targets, storage checklist, and evidence packaging.

What To Preserve

  • Hook points, class names, JNI symbols, signer inputs and outputs, and header names
  • Shared prefs, local DB rows, deeplinks, exported components, and token storage paths
  • The smallest replayable request or branch that proves the trust boundary

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 Competition Android Hooking AI skill do?

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Android APK hooking, Frida tracing, request-signing recovery, SSL pinning bypass, JNI boundary inspection, and app trust-boundary analysis. Use when the user asks to hook an APK, inspect signer logic, trace Java or native boundaries, bypass pinning or root checks, inspect shared prefs or app databases, or replay accepted mobile requests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Why use Competition Android Hooking on TypingMind?

Because you install it once and use it with any model. Competition Android Hooking 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 Competition Android Hooking in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-android-hooking. 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 Competition Android Hooking?

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 Competition Android Hooking?

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

Is the Competition Android Hooking AI skill free?

Yes. It is published on GitHub by zhaoxuya520 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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