Phishing Defender is a Python-based project that aims to protect users from phishing attacks🚫 by analyzing links on a webpage. The project utilizes web scraping techniques with Beautiful Soup to extract links from a given webpage. These extracted links are then sent to a new page, where a machine learning model🧠 predicts whether each link is phishing or legitimate based on various parameters.
- Web scraping using Beautiful Soup to extract links from a webpage.
- Integration with a machine learning model to predict the phishing or legitimate status of each link.
- Output display of links along with their corresponding status on a separate window.
Make sure you have the following dependencies installed:
- Python
- Beautiful Soup
- Flask (for the web application)
- Machine learning model dependencies (ensure you follow the model setup instructions)
- Any Code Editor (VS Code, Pycharm)
- Clone the repository:
git clone https://github.com/varunpareek690/phishing-defender.git
cd phishing-defender- Install dependencies:
pip install -r requirements.txt- Follow the instructions in the model/README.md to train or set up the machine learning model.
Visit http://localhost:5000 in your web browser to use Phishing Defender.
- Visit any website or the demo website created in the "HACK2.0" folder.
- Go to your browser settings, navigate to "Extensions," turn on developer options, and load the unpacked extension from the extension directory, Phishing defencer in the project
- Run this command in the terminal
python popup.py- The flask server will go live on http://localhost:5000
- Click the extension icon and then click the "Scrape Links" button.
PHISHDEFEND.1.mp4
Paras Goyal
Shivam Sharma
Varun Pareek
This project is licensed under the MIT License - see the LICENSE file for details.
Special thanks to Random Forest Classifier for providing the pre-trained model. Inspired by the need for better phishing protection in the digital world. Feel free to contribute, report issues, or suggest improvements!