https://github.com/mxrch/penglab

🐧 Abuse of Google Colab for cracking hashes.
https://github.com/mxrch/penglab

Last synced: 1 day ago
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🐧 Abuse of Google Colab for cracking hashes.

• Host: GitHub
• URL: https://github.com/mxrch/penglab
• Owner: mxrch
• Created: 2019-12-02T22:05:47.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2023-07-17T00:21:49.000Z (over 1 year ago)
• Last Synced: 2024-10-14T15:04:46.946Z (about 2 months ago)
• Language: Jupyter Notebook
• Homepage: https://colab.research.google.com/github/mxrch/penglab/blob/master/penglab.ipynb
• Size: 52.7 KB
• Stars: 922
• Watchers: 27
• Forks: 141
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml

Awesome Lists containing this project

• awesome-password-cracking - Penglab - Abuse of Google Colab for cracking hashes. (Cloud)

README

        
# Penglab

Abuse of Google Colab for fun and profit. 🐧

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mxrch/penglab/blob/master/penglab.ipynb)

## What is it ?

**Penglab** is a ready-to-install setup on Google Colab for cracking hashes with an incredible power, really useful for CTFs. *(See benchmarks below.)*

It installs by default :

* Hashcat

* John

* Hydra

* SSH (with ngrok)

And now, it can also :

* Launch an integrated shell

* Download the wordlists Rockyou and HashesOrg2019 quickly !

You only need a Google Account to use Google Colab, and to use ngrok for SSH (optional).

## How to use it ?

1. Go on : https://colab.research.google.com/github/mxrch/penglab/blob/master/penglab.ipynb

2. Select "**Runtime**", "**Change runtime type**", and set "**Hardware accelerator**" to **GPU**.

3. Change the config by setting "**True**" at tools you want to install.

4. Select "**Runtime**" and "**Run all**" !

## What is Google Colab ?

Google Colab is a free cloud service, based on Jupyter Notebooks for machine-learning education and research. It provides a runtime fully configured for deep learning and free-of-charge access to a robust GPU.

## Benchmarks

#### Hashcat Benchmark :

```CUDA API (CUDA 10.1)

====================

* Device #1: Tesla P100-PCIE-16GB, 16017/16280 MB, 56MCU

OpenCL API (OpenCL 1.2 CUDA 10.1.152) - Platform #1 [NVIDIA Corporation]

========================================================================

* Device #2: Tesla P100-PCIE-16GB, skipped

Benchmark relevant options:

===========================

* --optimized-kernel-enable

Minimum password length supported by kernel: 0

Maximum password length supported by kernel: 55

Hashmode: 0 - MD5

Speed.#1.........: 27008.0 MH/s (69.17ms) @ Accel:64 Loops:512 Thr:1024 Vec:8

Minimum password length supported by kernel: 0

Maximum password length supported by kernel: 55

Hashmode: 100 - SHA1

Speed.#1.........:  9590.3 MH/s (48.61ms) @ Accel:8 Loops:1024 Thr:1024 Vec:1

Minimum password length supported by kernel: 0

Maximum password length supported by kernel: 55

```

#### Speedtest :

```Retrieving speedtest.net configuration...

Testing from Google Cloud (35.203.136.151)...

Retrieving speedtest.net server list...

Selecting best server based on ping...

Hosted by KamaTera INC (Santa Clara, CA) [11.95 km]: 28.346 ms

Testing download speed................................................................................

Download: 2196.68 Mbit/s

Testing upload speed......................................................................................................

Upload: 3.87 Mbit/s

```