awesome-game-security is a curated collection focused on security research for games and game software, including cheating, anti-cheat systems, debugging, and anti-debugging. It is intended for security researchers and developers studying or building game-protection tools. The catalogue entries provide skills for AI coding agents related to the repository’s security workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add gmh5225/awesome-game-security --skill game-hackinggit clone --depth 1 https://github.com/gmh5225/awesome-game-securityWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gmh5225/awesome-game-security/game-hacking)<a href="https://agentmods.dev/skills/gmh5225/awesome-game-security/game-hacking"><img src="https://agentmods.dev/badge/skills/gmh5225/awesome-game-security/game-hacking/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gmh5225/awesome-game-security/game-hacking"><img src="https://agentmods.dev/badge/skills/gmh5225/awesome-game-security/game-hacking.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00095 | $0.06657 |
| Opus 5 | $0.00048 | $0.03328 |
| Sonnet 5 | $0.00019 | $0.01331 |
| Haiku 4.5 | $0.00010 | $0.00666 |
Grade A, and why
game-hacking-techniques scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 755 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Game Hacking Techniques
Overview
This skill maps the offensive side of game-security threat models: what an attacker seeks to observe or control, which capability is required, and where defenses have visibility or authority. User-mode, kernel, hypervisor, device, visual, and network threats are alternative or combined paths, not a universal escalation sequence.
Attacker Capability and Defensive Coverage
For threats beyond local runtime access, use game-server-security for backend authority and transactional correctness, and game-supply-chain-security for build, release and mod trust. Each extends the attack taxonomy with its own prerequisites.
Read the attack surface map when comparing attack families or building a defense coverage matrix. It includes client-state exposure, manipulation, injection, privileged acquisition, visual/input automation, and abuse of server trust, with prerequisites and counterexamples.
For each relevant family, explain the attack objective and boundary before naming tools. Identify what the defender can actually observe, what control prevents or limits the behavior, and what remains uncertain. Distinguish read-only information abuse from state modification, and synthetic input from evidence of human intent. Avoid presenting a missing artifact as proof that an attack is undetectable.
Cross-reference DMA acquisition for host-driver versus device access, and network evidence for account/device association and reported restrictions.
Treat implementations, performance numbers, stealth rankings, and detection
claims as versioned threat-model examples rather than guarantees. Use
research-rigor when converting them into a
factual claim or defensive decision.
Repository Resource Selection
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today Changed · -19 lines · +30 tokens per session fe5ebbdf24c6
- 10d ago First seen · 774 lines · 65 tokens per session scan A 858b9583c011
game-hacking-techniques is a skill published in the GitHub repository gmh5225/awesome-game-security (3,495 stars, last pushed today), licensed MIT. It adds 95 tokens to every session and 6,657 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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