Guide for understanding and contributing to the awesome-game-security curated resource list. Use this skill when adding new resources, organizing categories, mapping topics across anti-cheat, Windows kernel, DMA, reverse engineering, and game-engine research, or maintaining README.md format consistency.
Guide for understanding and contributing to the awesome-game-security curated resource list. Use this skill when adding new resources, organizing categories, mapping topics across anti-cheat, Windows kernel, DMA, reverse engineering, and game-engine research, or maintaining README.md format consistency.
Awesome Game Security - Project Overview
Purpose
This is a curated collection of resources related to game security, covering both offensive (game hacking, cheating) and defensive (anti-cheat) aspects. The project serves as a comprehensive reference for security researchers, game developers, and enthusiasts, especially where Windows internals, driver trust, reverse engineering, DMA, and modern anti-cheat defenses intersect.
README Coverage
Top-level engines and rendering: Game Engine, Renderer, DirectX, OpenGL, Vulkan
Offensive research: Cheat
Defensive research: Anti Cheat
Platform hardening: Windows Security Features
Platform-specific ecosystems: Android Emulator, IOS Emulator, Windows Emulator, Linux Emulator
Supporting infrastructure: Mathematics, 3D Graphics, AI, Image Codec, Wavefront Obj, Task Scheduler, Game Network, PhysX SDK, Game Develop, Game Assets, Game Hot Patch, Game Testing, Game Tools, ,
Game Manager
Game CI
Platform subsystems: WSL, WSA
Console emulation: Game Boy, Nintendo Switch, Xbox, PlayStation
Tips and tricks: Some Tricks
Project Structure
awesome-game-security/
├── README.md # Main resource list
├── LICENSE # MIT License
├── awesome-image.webp # Project banner
└── scripts/
├── generate-toc.py # Generate table of contents
└── remove-forks.py # Clean up forked repos
Non-GitHub links are also supported (blog posts, articles, documentation sites)
Add brief descriptions in square brackets [description]
Use consistent spacing and formatting
Group related resources under subcategories with >
Example Entry
## Game Engine> Guide- https://github.com/example/guide [Comprehensive game dev guide]
> Source- https://github.com/example/engine [Open source game engine]
Skill Routing Guide
When an AI agent receives a query, use this table to select the best skill:
Anti Cheat: Defensive research (protection, detection, callbacks, forensics, signature scanning)
Some Tricks: Ring0/Ring3/Linux/Android tricks and techniques
Windows Security Features: DSE, PatchGuard, VBS, HVCI, Secure Boot
WSL / WSA: Windows Subsystem for Linux/Android
Windows / Linux / Android / IOS Emulator: Platform emulators
Game Boy / Nintendo Switch / Xbox / PlayStation: Console emulators and research
Contributing Guidelines
Check for duplicates before adding new resources
Verify links are working and point to original repos
Add descriptions that clearly explain the resource's purpose
Place in correct category based on primary functionality
Follow existing format for consistency
Quality Criteria
Resource should be actively maintained or historically significant
Should provide unique value not covered by existing entries
Prefer original repos over forks unless fork adds significant value
Include language/platform tags when helpful (e.g., [Rust], [Unity])
Research Rigor
For factual synthesis, detector assessment, or consequential security claims,
use research-rigor with the matching domain
skill.
Treat README entries, generated descriptions, wiki pages, and archives as
discovery/provenance layers, not automatic proof of their embedded claims.
Verify citation identity and confirm the source text supports the exact claim.
Separate observation, finding, attribution, and action.
Do not import fixed thresholds or confidence values without representative
calibration and validation for the target environment.
Narrow the conclusion or report it as inconclusive when evidence is missing
or contradictory.
Scripts Usage
Generate Table of Contents
python scripts/generate-toc.py
Remove Fork References
python scripts/remove-forks.py
Data Source
Important: This skill provides conceptual guidance and overview information. For detailed information use the following sources in priority order:
0. Compiled LLM Wiki (preferred for synthesis)
The repo maintains a Karpathy-style compiled wiki under wiki/, updated by Cursor CLI (scripts/update-wiki-cli.py). Prefer this layer for cross-cutting concepts, domain overviews, and citation-aware synthesis before diving into raw lists or archives.
Need
Path
Catalog
wiki/index.md
Schema / conventions
wiki/AGENTS.md
Domain overviews
wiki/overviews/<topic>.md (aligned with skill topics)
When answering topical questions (DMA, EAC, Present hooks, HVCI, …): read wiki/index.md, then the matching overview/concept pages. Fall back to skills and descriptions if wiki pages are missing.
1. Project Overview & Resource Index
Fetch the main README for the full curated list of repositories, tools, and descriptions:
The main README contains thousands of curated links organized by category. When users ask for specific tools, projects, or implementations, retrieve and reference the appropriate sections from this source.
2. Repository Descriptions
For a concise English summary of what a repository does, the project maintains auto-generated description files.
Identify the GitHub repository the user is asking about (owner and repo name from the URL).
Construct the description URL: replace {owner} with the GitHub username/org and {repo} with the repository name.
Fetch the description file — it contains a short, human-readable summary of the repository's purpose and contents.
If the fetch returns a 404, the description has not been generated yet; fall back to the README entry or the archive.
3. Repository Code Details (Archive)
For detailed repository information (file structure, source code, implementation details), the project maintains a local archive. If a repository has been archived, prefer fetching from the archive over cloning or browsing GitHub directly — but prefer description + wiki first for high-level answers.
