DevPostHacakathon - Phishing Detector -_Phish-n-Chips

Overview Phish & Chips is a machine learning-based phishing detection system that:

• Trains a Random Forest model to identify phishing websites.
• Deploys as a Flask API for real-time detection.
• Integrates with a Firefox browser extension to alert users.

Installation & Setup 1️⃣ Setting Up the Training Environment Requirements Ensure you have Python 3.8+ installed, then install dependencies:

pip install -r requirements.txt

Training the Model

python train_model.py

2️⃣ Running the Flask API Start the API

python app.py

This launches the API at http://localhost:5000, where you can send URLs for phishing analysis. Test the API

curl -X POST http://localhost:5000/predict -H "Content-Type: application/json" -d '{"url": "https://example.com"}'

3️⃣ Installing the Browser Extension (Firefox) Steps:

1. Open Firefox and go to about:debugging/runtime/this-firefox.
2. Click "Load Temporary Add-on."
3. Select the manifest.json file from the browser_extension/ folder.
4. The extension icon should appear in your browser toolbar. Using the Extension

• Green ✅ = Legitimate site
• Red ⚠️ = Phishing detected
• Warning Page 🚨 = High-risk phishing site

Usage

• Train the model (train_model.py).
• Run the API (app.py).
• Install and test the browser extension.
• Monitor logs for debugging and improvements.