🛡️ PhishGuard Web App

PhishGuard Web App is a machine learning-powered phishing detection tool that allows users to check whether a URL is safe or potentially malicious — directly from a simple web interface.

Unlike the browser extension, this version works as a standalone web application, making it easy to test and use across any device.

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🌐 Live Demo

🔗 Try the app here:
https://phishguard-extension-pb9ahd84x4tbbu8djkrxqj.streamlit.app/

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🚀 Features

• 🔍 Detect phishing URLs instantly
• 🤖 Machine Learning-based prediction
• 🌐 Simple and clean web interface (Streamlit)
• ⚡ Fast and lightweight
• 📊 Real-time results

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🧠 How It Works

1. User enters a URL
2. The model extracts relevant features
3. ML model analyzes the URL
4. Returns:
   • ✅ Safe
   • ⚠️ Suspicious / Phishing

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🛠️ Tech Stack

• Frontend: Streamlit
• Backend: Python
• ML Model: Scikit-learn
• Libraries: Pandas, NumPy

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📂 Project Structure

phishguard-web/
│── index.html
│── streamlit_app.py
│── requirements.txt

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⚙️ Installation & Setup

1. Clone the repository

git clone https://github.com/your-username/phishguard.git
cd phishguard/phishguard-web

2. Create virtual environment (optional but recommended)

python -m venv venv
venv\Scripts\activate   # Windows

3. Install dependencies

pip install -r requirements.txt

4. Run the app

streamlit run streamlit_app.py

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🌐 Usage

• Open the app in your browser
• Enter any URL
• Click Check
• View prediction result instantly

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📌 Example

Input:

http://fake-login-page.xyz

Output:

⚠️ This website is likely a phishing site

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🎯 Future Improvements

• 🔐 Add real-time API integration
• 📱 Improve UI/UX
• 📊 Show confidence score
• 🌍 Deploy on cloud (Streamlit Cloud / Vercel backend)

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🤝 Contributing

Contributions are welcome!

1. Fork the repo
2. Create a new branch
3. Make changes
4. Submit a Pull Request

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📜 License

This project is open-source and available under the MIT License.