MobileRE-Skill — security grade SAFE, quality 64/100

Security audit verdict: SAFE · quality 64/100

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 index-login · MCP Server · ★ 81

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is MobileRE-Skill safe to install? View the security audit →

About MobileRE-Skill

MobileRE-Skill — 综合移动端逆向分析 Agent 技能集 一个让 AI Agent(Kilo)真正"会逆向"的完整技能系统 —— 不只是 Frida 脚本,而是覆盖静态分析、动态分析、脱壳、反检测、Native 逆向、安全合规的完整逆向工作流。 English README · English 如果这个项目对你有帮助,欢迎 ⭐ Star 支持! 使用场景 你只需要用一句话描述需求,AI 按决策树自动完成整个分析流程: "看下这个 Ap

agent-skillsai-agentandroid-securityanti-debugdexdynamic-instrumentationfridafrida-scriptsfrida-skillsghidra

Quick Facts

Stars81
Forks22
LanguageJavaScript
CategoryMCP Server
LicenseMIT
Quality Score63.8853351055573/100
Last Updated2026-09-30
Created2026-06-01
Platformsmcp, node
Est. Tokens~15k

Compatible Skills

These tools work well together with MobileRE-Skill for enhanced workflows:

  • areclaw — semantic(0.45)+complementary+rare_topics+same_lang+similar_pop+shared_platform (79%)
  • android-reverse-engineering-skill — semantic(0.49)+complementary+rare_topics+same_lang+similar_pop+shared_platform (72%)
  • rev-skills — semantic(0.30)+complementary+rare_topics+same_lang+similar_pop+shared_platform (69%)
  • PerimeterX_RE — semantic(0.31)+complementary+same_lang+similar_pop+shared_platform (61%)

MobileRE-Skill alternative? Top 6 similar tools

Looking for a MobileRE-Skill alternative? If you're comparing MobileRE-Skill with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • reverse-engineering-is-over by yasminefolo · ⭐ 116

    LLMs have ended reverse engineering as a high-barrier skill. Case study: reconstructing 6/7 custom HTTP signin

  • frida-analykit by ZSA233 · ⭐ 152

    Frida 工具包 - 主要面向安卓端逆向,解决frida环境版本管理和对Agent端常用底层工具方法封装,支持MCP。(目前主要由AI开发维护代码)

  • RivalSearchMCP by damionrashford · ⭐ 131

    Deterministic research MCP server on FastMCP 3 — 5-engine web search, 9-platform social search, 6 academic DBs

  • deterministic-agent-control-protocol by elliot35 · ⭐ 88

    Governance gateway for AI agents — bounded, auditable, session-aware control with MCP proxy, shell proxy & HTT

  • areclaw by TheQmaks · ⭐ 61

    Android Reverse Engineering Command-Line Automation Workspace. AI-driven security analysis with Claude Code.

  • BinAssistMCP by symgraph · ⭐ 51

    Binary Ninja plugin to provide MCP functionality.

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Frequently Asked Questions

What is MobileRE-Skill?

MobileRE-Skill is AI Agent 驱动的移动端逆向技能集:Frida hook、一键脱壳、反检测绕过、内存 DEX dump、Ghidra MCP 符号/结构恢复。AI-agent skill system for mobile reverse engineering.. It is categorized as a MCP Server with 81 GitHub stars.

What programming language is MobileRE-Skill written in?

MobileRE-Skill is primarily written in JavaScript. It covers topics such as agent-skills, ai-agent, android-security.

How do I install or use MobileRE-Skill?

You can find installation instructions and usage details in the MobileRE-Skill GitHub repository at github.com/index-login/MobileRE-Skill. The project has 81 stars and 22 forks, indicating an active community.

What license does MobileRE-Skill use?

MobileRE-Skill is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to MobileRE-Skill?

The top alternatives to MobileRE-Skill on Agent Skills Hub include reverse-engineering-is-over, frida-analykit, RivalSearchMCP. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

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