ags-anti-sandbox

ags-anti-sandbox is a skill for Claude Code, Codex from 1llu50ry/mcp-gamehacking. It costs 27 tokens per session (180 once invoked), scanned A, original, MIT.

A Windows proof of concept that detects signs of Any.Run-like sandbox environments. A sandbox is an isolated system used to run and inspect potentially harmful software.

In plain words
What is it for?
It checks folders, running processes, user-profile details, services, and drivers, and reports a match only when multiple indicators fit expected sandbox traits.
Why use it?
It demonstrates how software can identify automated analysis environments by combining several host clues. This is useful for studying malware behavior and sandbox-aware evasion, not for ordinary application development.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It checks folders, running processes, user-profile details, services, and drivers, and reports a match only when multiple indicators fit expected sandbox traits.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/1llu50ry/mcp-gamehacking/ags-anti-sandbox
Install

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.

Any agent
npx skills add 1llu50ry/mcp-gamehacking --skill ags-anti-sandbox
Clone the repo
git clone --depth 1 https://github.com/1llu50ry/mcp-gamehacking

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for ags-anti-sandbox

README.md
[![agentmods](https://agentmods.dev/badge/skills/1llu50ry/mcp-gamehacking/ags-anti-sandbox/github.svg)](https://agentmods.dev/skills/1llu50ry/mcp-gamehacking/ags-anti-sandbox)
Your own site
<a href="https://agentmods.dev/skills/1llu50ry/mcp-gamehacking/ags-anti-sandbox"><img src="https://agentmods.dev/badge/skills/1llu50ry/mcp-gamehacking/ags-anti-sandbox/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.

agentmods 80×15 button for ags-anti-sandbox

Your own site · 80×15
<a href="https://agentmods.dev/skills/1llu50ry/mcp-gamehacking/ags-anti-sandbox"><img src="https://agentmods.dev/badge/skills/1llu50ry/mcp-gamehacking/ags-anti-sandbox.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 180 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00027 $0.00180
Opus 5.5 $0.00011 $0.00072
Sonnet 5.5 $0.00005 $0.00036
Haiku 4.5 $0.00003 $0.00018

Measured 2d ago against content hash 754b0705e73d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ags-anti-sandbox 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 2d ago.

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.

skills/ags-anti-sandbox/SKILL.md · 20 lines

What it actually says

Anti Sandbox

Author: SaadAhla Source: mcp-gamehacking/skills/ags-anti-sandbox

Description

This project is a small Windows proof of concept for detecting Any.Run-like sandbox environments using host artifact checks. It is written in C++ and combines folder presence checks, process enumeration, user-profile heuristics, and service or driver lookup logic. The sample triggers a detection result only when multiple indicators match expected sandbox traits, demonstrating a layered evasion approach. It is intended for malware analysis research and for understanding how sandbox-aware code can evade automated inspection.

Files

What ships with it

1 file 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.

Changes

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.

  1. 2d ago First seen · 20 lines · 27 tokens per session scan A 754b0705e73d

Subscribe to this mod's changes

ags-anti-sandbox is a skill published in the GitHub repository 1llu50ry/mcp-gamehacking (344 stars, last pushed 2d ago), licensed MIT. It adds 27 tokens to every session and 180 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-23.

Related

Other skills, from other repositories

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

component-fixtures

Use when creating or updating component fixtures for screenshot testing or their shared infrastructure, or when designing UI components to be fixture-friendly. Covers fixture file structure, theming, service setup, CSS scoping, async rendering, validation, and common pitfalls.

microsoft/vscode · 53 tokens