Crackq

pip install cognis-crackq
crackq run --hash 5f4dcc3b5aa765d61d8327deb882cf99 --algorithm md5 --words password   # → cracked in ms

Watch the walkthrough

A full narrated tour — setup, the tool in action, and every demo scenario:

Watch the crackq walkthrough

▶ Watch the walkthrough (MP4)

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ crackq-emit --version
crackq 0.1.0

$ crackq-emit --help
usage: crackq [-h] [--version] [--format {table,json}] [--audit-log AUDIT_LOG]
              {run,audit,algos} ...

Self-hosted password cracking queue.

positional arguments:
  {run,audit,algos}
    run                 submit hashes and drain the queue
    audit               print or verify the audit log
    algos               list supported algorithms

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  --format {table,json}
  --audit-log AUDIT_LOG

Blocks above are real crackq output — reproduce them from a clone.

Sample result format (illustrative values — run on your own data for real findings):

{
"findings": [
    {
        "id": "1234567890",
        "title": "Suspicious Network Traffic",
        "description": "Anomalous network traffic detected from 192.168.1.100 to 8.8.8.8",
        "severity": "medium",
        "created_at": "2023-02-20T14:30:00Z"
    }
]
}

Usage — step by step

Defensive / authorized password-recovery only. Use on hashes you own or are explicitly authorized to test.

1. Install the CLI (Python 3.9+):

   pip install crackq         # or: pip install .   from a checkout
   

2. List supported algorithms first:

   crackq algos
   

3. Submit hashes and drain the queue in one shot — the run subcommand submits + runs + reports against a wordlist:

   crackq run --hash 5f4dcc3b5aa765d61d8327deb882cf99 --algorithm md5 --wordlist rockyou.txt --owner blue-team
   

   You can repeat --hash, supply --hashfile, pass inline --words, or use --no-rules to disable rule mangling.

4. Read the result — --format json gives per-job state; exit code is 1 if any job failed (bad algo/error), 0 otherwise. Verify the tamper-evident audit log:

   crackq run --hashfile hashes.txt --wordlist rockyou.txt --format json | jq '.[] | {hash, state, plaintext}'
   crackq audit --verify
   

5. Use it in an authorized credential-audit pipeline — every action is appended to the audit log (default in the temp dir; override with --audit-log):

   crackq --audit-log audit.jsonl run --hashfile hashes.txt --wordlist words.txt --owner soc
   

Contents

• Why crackq? · Features · Quick start · Example · Architecture · Demos · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing

Why crackq?

Self-hosted password cracking queue — multi-user hashcat with audit log — without standing up heavyweight infrastructure.

crackq is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.

Features

• ✅ Supported Algorithms
• ✅ Detect Algorithm
• ✅ Crack Hash
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

pip install cognis-crackq
crackq --version
crackq algos                                                   # list supported algorithms
crackq run --hash <digest> --wordlist words.txt --owner blue   # submit + drain the queue
crackq run --hashfile hashes.txt --wordlist words.txt --format json   # machine-readable
crackq audit --verify                                          # check the tamper-evident log

Example

$ crackq run --hashfile hashes.txt --wordlist words.txt --owner blue-team
hash              owner      algorithm  state      plaintext  candidates_tried
----------------  ---------  ---------  ---------  ---------  ----------------
201f00b5ca5d...   blue-team  md5        cracked    welcome1   74
17e689a225fa...   blue-team  sha256     exhausted             255

$ crackq audit --verify
verified: True
records: 5

Architecture

flowchart LR
  IN[hashes + owner + priority] --> Q[CrackQ<br/>priority queue]
  WL[(wordlist)] --> ENG[crack_hash<br/>dictionary + rules]
  Q --> ENG
  ENG --> OUT[jobs: cracked / exhausted<br/>JSON / table]
  Q --> AUD[(hash-chained audit log)]

See docs/ARCHITECTURE.md for the full design.

Demos

Five runnable, offline scenarios in demos/ — each targets a different audience and uses the real crackq API (no network, no external engine). They exit 0 and double as smoke tests. See docs/DEMOS.md.

PYTHONUTF8=1 python demos/run_all.py                       # all five
PYTHONUTF8=1 python demos/02_secops_priority_queue.py      # or just one

#	Scenario	Audience	Shows
1	01_red_team_recovery.py	Red teams / pentesters	Queue a dump, crack with rules, report per-account verdicts
2	02_secops_priority_queue.py	Security operations	Multi-user priority scheduling; incident jumps the line
3	03_ir_audit_chain.py	Incident response / compliance	Tamper-evident audit chain; verify() catches a forged record
4	04_platform_admin_capacity.py	Queue / platform admins	Candidate counts + timing — the cost of rules
5	05_cli_pipeline.py	Automation / CI	Drive the real CLI, parse JSON, feed downstream tooling

Authorized / defensive use only — every demo hash is generated from a known plaintext we own.

Use it from any AI stack

crackq is interoperable with every popular way of using AI:

• MCP server — crackq mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe crackq scan . --format json into any agent or LLM
• LangChain · CrewAI · AutoGen · LlamaIndex — wrap the CLI/JSON as a tool in one line
• CI / scripts — exit codes + SARIF for non-AI pipelines

How it compares

	Cognis crackq	typical tools
Self-hostable, no account	✅	varies
Single command, zero config	✅	⚠️
JSON + SARIF for CI	✅	varies
MCP-native (AI agents)	✅	❌
Polyglot ports (JS/Go/Rust)	✅	❌
Open license	✅ COCL	varies

Integrations

Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (crackq mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.

Install — every way, every platform

pip install "git+https://github.com/cognis-digital/crackq.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/crackq.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/crackq.git" # uv
pip install cognis-crackq                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/crackq:latest --help        # Docker
brew install cognis-digital/tap/crackq                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/crackq/main/install.sh | sh

Linux	macOS	Windows	Docker	Cloud
scripts/setup-linux.sh	scripts/setup-macos.sh	scripts/setup-windows.ps1	docker run ghcr.io/cognis-digital/crackq	DEPLOY.md (AWS/Azure/GCP/k8s)

Related Cognis tools

• c2detect — C2 server fingerprinter — Cobalt Strike, Sliver, Mythic, Havoc, Brute Ratel
• payloadlab — Static malicious payload analyzer — PE/ELF/LNK/macro/OneNote
• redpath — Active Directory attack path mapper — minimum-cost paths + remediation priority
• pwnreview — Pentest report generator — YAML findings to CREST-grade PDF

Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram

Contributing

PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.

⭐ If crackq saved you time, star it — it genuinely helps others find it.

Interoperability

{} composes with the 300+ tool Cognis suite — JSON in/out and a shared OpenAI-compatible /v1 backbone. See INTEROP.md for the suite map, composition patterns, and reference stacks.

License

Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license ([email protected]). See LICENSE.

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