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CrackQ

Author: Daniel Turner @f0cker_


Python 3 REST API & JS GUI for managing hashcat crack jobs in a queuing system.

PyPI license Quality Gate Status Security Rating Blackhat Arsenal Europe 2019

CrackQ Dashboard

Feature List

  • REST API
  • Remote Python client or JS GUI
  • Cracked passwords analysis and reporting, including AD dump analysis
  • Uses Hashcat API directly via libhashcat, no shell commands
  • Easy installation using docker containers
  • SQL, LDAP or SAML2 Authentication
  • Multi-user support with privilege separation for jobs
  • Job queues with pause/restore/move
  • Always supports the latest Hashcat version and algorithms
  • Email notifications when a hash cracks or job finishes
  • Intelligent queuing, new jobs added to the queue undergo a speed/show check immediately and will instantly show previously cracked hashes from the pot file without waiting
  • Automated Brain integration, Brain activates when it becomes efficient (uses above speed check)
  • Detailed job stats/charts for active jobs
  • Preconfigured rate-limiting
  • Markov stats pre-configured
  • Sample mask files included
  • Hashcat benchmark visualisations
  • Templates & Tasks allow you to save preset cracking techniques to create grouped jobs
  • Potfile++ - a wordlist automatically updated from the potfile daily can be optionally used with each job

Requirements

This tool has the following requirements:

  • Drivers

    • OpenCL drivers - these can be installed from a repository or downloaded from the relevant vendor. Tested using Intel runtime.
    • Nvida drivers
    • AMD drivers
  • Docker

  • Nvidia-runtime

  • Docker-compose

It is recommended to have a hefty server build with ample RAM/CPU power. However, the application has been tested on a VM with 8 cores and 4GB RAM so there should not be any issues with resources given that the server will need a good amount of resources for cracking anyway.

See the Wiki for installation and guides and Discord channel invite.