Leaderboard/Security/reverse-skill
Last commit on August 8, 2026·Created on May 13, 2026

zhaoxuya520/reverse-skill

A specialized toolkit for analyzing AI agent vulnerabilities and Active Directory certificate abuse.
Combined rank
#24
across all skills
In Security
#1
category rank
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TL;DR

This repository provides structured workflows for security researchers investigating prompt-to-tool flows, retrieval poisoning, and supply-chain challenges. It focuses on the technical intersection of AI agent orchestration and traditional security boundaries.

The skill set extends to deep infrastructure analysis, including the exploitation of AD CS certificate templates and the bypass of SSL pinning in Android environments.

WHO IT'S FOR
Security researchers
analyzing Android APK hooking and Frida tracing
Penetration testers
exploiting AD CS certificate templates and EKUs
Cloud security engineers
analyzing prompt-injection and supply-chain challenges
CTF competitors
automating security challenges via AI coding clients
Repository contents

89 skill files

Compatible AgentsThe repository documents support for these agents. The skills may also work with other agents that can load SKILL.md files, but they may need some setup or small changes.

Use this skill collection

Follow the documented setup, then try a first task.

I’m using

Full bundle on Windows

Installs: Complete reverse-skill cybersecurity skills router bundle, including the documented skills beyond the bounded skillPaths selection below. · Claude Code, Codex, Cursor, OpenCode, Cline, Windsurf, Kiro

Before you start
  • Java / JDK
  • Node.js 22.12+
  • Python 3.x
  • A code AI client such as Claude Code, Codex, Cursor, OpenCode, or another compatible client

Platform: Windows

Run from: The cloned reverse-skill repository root—the directory containing README.md

  1. In a terminal, clone the complete repository.

    git clone https://github.com/zhaoxuya520/reverse-skill.git
  2. From the cloned repository root, run the Windows tool-index refresh command in a terminal.

    powershell -File skills/scripts/refresh-tool-index.ps1
README.md · Checked Sep 18, 2026README_AI.md · Checked Sep 18, 2026

Give it something to do.

Suggested first task

Passively triage an authorized binary

Uses binary-ninja-reverse

  • Authorized local binary path replacing <binary-path>
  • Confirmed case scope
  • Binary Ninja installation with a valid Vector 35 license
Use the binary-ninja-reverse skill to perform passive triage of the authorized local binary at <binary-path>. Confirm the case scope, verify that Binary Ninja is installed with a valid license, and work from a copy. Report the file hash, architecture, entry points, segments, imports, exports, representative strings, and a few preliminary cross-reference observations. Do not patch the binary or save modifications.
README.md · Checked Sep 18, 2026skills/binary-ninja-reverse/SKILL.md · Checked Sep 18, 2026
Suggested first task

Create and review a first SBOM

Uses supply-chain-security

  • Authorized local project path replacing <project-path>
  • Confirmed assessment scope
  • An available SBOM tool recorded in the repository tool index
Use the supply-chain-security skill to review the authorized local project at <project-path>. Check the repository tool index first. If a documented SBOM tool is already available, generate one SBOM and provide a short audit covering unknown or unmaintained dependencies, license conflicts, and direct versus transitive dependencies. If no suitable tool is available, report the missing prerequisite and stop without installing anything, uploading artifacts, or changing the project.
README.md · Checked Sep 18, 2026skills/supply-chain-security/SKILL.md · Checked Sep 18, 2026
Suggested first task

Map an LLM application's attack surface

Uses llm-security

  • Architecture, configuration, or design-document path replacing <architecture-path>
  • Confirmed authorization and assessment scope
Use the llm-security skill to create a passive attack-surface map for the authorized LLM application described by <architecture-path>. Identify its LLM-facing entry points, registered tools and parameters, data flow from user input through retrieval and tool calls to outputs, possible system-prompt leakage surfaces, and human-approval gates. Do not send attack payloads or invoke application tools.
README.md · Checked Sep 18, 2026skills/llm-security/SKILL.md · Checked Sep 18, 2026