someshkar/colabcat
Running Hashcat on Google Colab with session backup and restore.
repo name | someshkar/colabcat |
repo link | https://github.com/someshkar/colabcat |
homepage | |
language | Jupyter Notebook |
size (curr.) | 24 kB |
stars (curr.) | 181 |
created | 2020-06-08 |
license | MIT License |
Colabcat
Run Hashcat on Google Colab with session restore capabilities with Google Drive.
Usage
- Go to the link below to open a copy of the
colabcat.ipynb
file in Google Colab: https://colab.research.google.com/github/someshkar/colabcat/blob/master/colabcat.ipynb - Click on
Runtime
,Change runtime type
, and setHardware accelerator
to GPU. - Go to your Google Drive and create a directory called
dothashcat
, with ahashes
subdirectory where you can store hashes. - Come back to Google Colab, click on
Runtime
and thenRun all
. - 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
!bash
in 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 .restore
, .log
and the .potfile
files across Google Colab sessions by storing them in your Google Drive.
Benchmarks
The 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
Similar projects
- mxrch/penglab : This is great if you’re looking to use other tools like John and Hydra on Colab too.
Contributing
Issues and Pull Requests are always welcome. Feel free to contribute new Colab GPU benchmarks and features.