Follow the steps below to bulild and use crackerjack in a docker container supported by GPU (Nvidia).
To get started, clone the repository and use Docker to build the Docker image.
sudo docker build . -t hweb --network=host
You can save a Docker image to copy to another machine by using the save
command.
sudo docker save --output="hweb_latest.tar" hweb:latest
The image will be saved as a tar file.
To use the image on a new machine you can import the content from an archive.
sudo docker load -i ./hweb_latest.tar
Create the HWEB folder to use it together with the crackerjack service. Create folders listed below: hashcat, rule, hashfile, wordlistst, masks.
- hashfile is intended for large hashfiles.
- rule (and masks) is a folder for hashcat rules files.
- wordlists is a folder containing password dictionaries
Start your container using the docker run command.
sudo docker run -d -p 8080:5000 -v "$PWD/HWEB":/root/HWEB hweb:latest
Configure the parameters to work with the service according to the picture.
Use the following comands to set up CUDA.
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \ && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \ && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list sudo apt-get update sudo apt-get install -y nvidia-docker2 sudo systemctl restart docker
apt-get download $(apt-cache depends --recurse --no-recommends --no-suggests --no-conflicts --no-breaks --no-replaces --no-enhances nvidia-docker2 | grep "^\w" | sort -u | grep -v i386)
docker run -d --gpus all -p 8080:5000 -v "$PWD/HWEB":/root/HWEB hweb:latest