# crackq

> crackq — cognis-digital-crackq. Use this tool when you need to manage and audit password cracking tasks across multiple users, leveraging the power of hashcat in a self-hosted environment with a robust audit log. It solves problems of scalability, security, and accountability in password recovery processes. Ideal for use cases requiring centralized management of password cracking queues with transparent logging and multi-user support.

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

## Description

Self-hosted password cracking queue — multi-user hashcat with audit log

## 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/crackq)

## 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-crackq"
    }
  }
}
```

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