The primary objective of this project is to effectively model phishing website characteristics using Generative Adversarial Networks, and use it to detect phishing attacks. We use only the visual and textual characteristics of the phishing website to model the attacker's signature. The primary use-case of this idea would primarily be for situations which require expedited re-training of the neural network, which would otherwise take a significantly longer time, when using large amounts website metadata for formulating the signature. The extended re-training time required is a significant attack vector which could be exploited by malicious agents.
Please check the progress report here for detailed information, and goals achieved.
- Python 3: https://www.python.org/download/releases/3.0/
- TensorFlow 2: https://www.tensorflow.org/
- PyTorch: https://pytorch.org/
- Jupyter Notebook: https://jupyter.org/
- Python 3: https://www.python.org/download/releases/3.0/
- TensorFlow 2: https://www.tensorflow.org/
- PyTorch: https://pytorch.org/
- Anaconda distribution: https://www.anaconda.com/products/individual
To install, clone the repo to your local machine:
git clone https://github.com/vignesh-pagadala/phishing-detection-gan.git
To reproduce, run the code through the Jupyter Notebooks:
cd docs/Notebooks/
jupyter-notebook DCGAN-Implementation-1.ipynb
See the open issues for a list of proposed features (and known issues).
- Top Feature Requests (Add your votes using the 👍 reaction)
- Top Bugs (Add your votes using the 👍 reaction)
- Newest Bugs
Reach out to the maintainer at one of the following places:
- GitHub issues
- The email which is located in GitHub profile
If you want to say thank you or/and support active development of Phishing Detection GAN:
- Add a GitHub Star to the project.
- Tweet about the Phishing Detection GAN on your Twitter.
- Write interesting articles about the project on Dev.to, Medium or personal blog.
Together, we can make Phishing Detection GAN better!
First off, thanks for taking the time to contribute! Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make will benefit everybody else and are greatly appreciated.
We have set up a separate document containing our contribution guidelines.
Thank you for being involved!
The original setup of this repository is by Vignesh Pagadala.
For a full list of all authors and contributors, check the contributor's page.
Phishing Detection GAN follows good practices of security, but 100% security can't be granted in software. Phishing Detection GAN is provided "as is" without any warranty. Use at your own risk.
For more info, please refer to the security.
This project is licensed under the Apache Software License 2.0.
See LICENSE for more information.