game-hacking-techniques

Classify game-cheat capabilities and their defensive implications across memory.

What this skill does for you

Classify game-cheat capabilities and their defensive implications across memory, injection, rendering, input, engines, kernels, DMA, and remote transports. Use for authorized threat modeling, not operational deployment.

Quoted from the skill description in the pinned source

Who made it

Publishergmh5225

Repositoryawesome-game-security

Installs284as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the game-hacking-techniques skill from gmh5225/awesome-game-security.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: b59f35ee0c1e5aa9df21dc9603bdf7198348cc1b. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: b59f35ee0c1e5aa9df21dc9603bdf7198348cc1b. Raw findings: 1. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: b59f35ee0c1e5aa9df21dc9603bdf7198348cc1b. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/gmh5225/awesome-game-security
Pinned skill file: View source at revision
Revision: b59f35ee0c1e5aa9df21dc9603bdf7198348cc1b
Package hash: sha256:75965b988fd793fe8d61fef2c9dab92bd960e3a1edbeb19d2f477359f7d57f91
Licence: MIT