Awesome

CrackQ

Author: Daniel Turner @f0cker_

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

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.