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https://github.com/f0cker/crackq

CrackQ: A Python Hashcat cracking queue system
https://github.com/f0cker/crackq

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CrackQ: A Python Hashcat cracking queue system

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README

        

CrackQ
============

Author: Daniel Turner
@f0cker_

------------

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

[![PyPI license](https://img.shields.io/pypi/l/ansicolortags.svg)](https://pypi.python.org/pypi/ansicolortags/)
[![Quality Gate Status](https://sonarcloud.io/api/project_badges/measure?project=f0cker_crackq&metric=alert_status)](https://sonarcloud.io/api/project_badges/measure?project=f0cker_crackq&metric=alert_status)
[![Security Rating](https://sonarcloud.io/api/project_badges/measure?project=f0cker_crackq&metric=security_rating)](https://sonarcloud.io/dashboard?id=f0cker_crackq)
![Blackhat Arsenal Europe 2019](https://img.shields.io/badge/Black%20Hat%20Arsenal-Europe%202019-blue.svg)

![CrackQ Dashboard](docs/crackq_dash.jpg)

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](https://github.com/f0cker/crackq/wiki) for installation and guides and Discord channel invite.