# binhunt

> binhunt — cognis-digital-binhunt. Use this tool when you need to scan game or desktop binaries for integrity and detect potential tampering, taking executable files as input and outputting fingerprints, packer/obfuscator detection, and diff results against a known-good baseline. It solves problems related to binary security and authenticity, helping to identify malicious modifications. Ideal for use in development, testing, and security auditing contexts.

Canonical page: https://skillsregistry.net/skills/cognis-digital-binhunt  
JSON: https://api.skillsregistry.net/v1/skills/cognis-digital-binhunt

## Description

Game/desktop binary integrity scanner that fingerprints executables, detects common packers/obfuscators, and diffs against a known-good baseline to catch tampering.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/cognis-digital/binhunt)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "cognis-digital-binhunt"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cognis-digital-binhunt` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cognis-digital-binhunt/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt