CrackQ
Python 3 REST API & JS GUI for managing hashcat crack jobs in a queuing system.
Author: Daniel Turner @f0cker_
Feature List
- REST API
- Remote Python client or JS GUI
- Cracked passwords analysis and reporting
- 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
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.
