- Go to the link below to open a copy of the
colabcat.ipynbfile in Google Colab: https://colab.research.google.com/github/someshkar/colabcat/blob/master/colabcat.ipynb
- Click on
Change runtime type, and set
Hardware acceleratorto GPU.
- Go to your Google Drive and create a directory called
dothashcat, with a
hashessubdirectory where you can store hashes.
- Come back to Google Colab, click on
- When it asks for a Google Drive token, go to the link it provides and authenticate with your Google Account to get the token.
- You can edit the last few cells in the notebook to customize the wordlists it downloads and the type of hash it cracks. A full list of these can be found here.
- If needed, simply type
!bashin a new cell to get access to an interactive shell on the Google Colab instance.
How it works
Colabcat creates a symbolic link between the
dothashcat folder in your Google Drive and the
/root/.hashcat folder on the Google Colab session.
This enables seamless session restore even if your Google Colab gets disconnected or you hit the time limit for a single session, by syncing the
.log and the
.potfile files across Google Colab sessions by storing them in your Google Drive.
benchmarks directory in this repository lists
.txt files with hashcat benchmarks run with
hashcat -b. The list of known Google Colab GPUs are listed below. An up to date list can be found in the Colab FAQ.
- Nvidia Tesla K80
- Nvidia Tesla T4
- Nvidia Tesla P4
- Nvidia Tesla P100
- mxrch/penglab : This is great if you're looking to use other tools like John and Hydra on Colab too.
Issues and Pull Requests are always welcome. Feel free to contribute new Colab GPU benchmarks and features.