FAKE URL DETECTOR🕵️🎯

A modern web application that analyzes URLs to detect potential phishing attempts using machine learning and security features analysis.

🔒 Features

• Modern UI Design: Sleek dark theme with vibrant orange accents for a professional tech aesthetic
• ML-Powered Phishing Detection: Advanced algorithms to identify fraudulent URLs with high accuracy
• Detailed Security Analysis: Comprehensive breakdown of URL security features and potential vulnerabilities
• Real-time Validation: Instant feedback as you type with smart URL suggestions
• Enhanced Trust Indicators: Visual confidence metrics for legitimate domains with animated elements
• Responsive Design: Fully optimized for all devices from desktop to mobile
• Advanced Error Handling: User-friendly error messages with helpful recommendations
• Live Security Dashboard: Real-time metrics showing threat statistics and protection status

Installation

1. Clone the repository
2. Install the required dependencies:

pip install -r requirements.txt

3. If you encounter dependency issues, particularly with dnspython, you can install it separately:

pip install dnspython==2.2.1

How to Run

Using the Full Application

Start the Flask application:

python app.py

Using the Offline Demo Version

If you have issues with the Python dependencies or just want to see the UI in action:

1. Navigate to the static folder
2. Open offline_demo.html in your web browser

The offline demo provides a simulated experience of the application without requiring the server to be running.

Troubleshooting

Missing DNS Module

If you see an error like ModuleNotFoundError: No module named 'dns', install the dnspython package:

pip install dnspython==2.2.1

Invalid Escape Sequence Warning

You might see warnings about invalid escape sequences in regex patterns. These have been fixed in the latest version.

Server Not Running

If you receive errors indicating that the server is not responding:

1. Check that you have all dependencies installed
2. Verify that the Flask application is running
3. Try using the offline demo version to see the UI

Technologies Used

• Python Flask for the backend
• Bootstrap 5 for responsive layout
• Custom CSS for modern tech UI
• JavaScript for interactive features
• Machine learning for phishing detection

License

This project is licensed under the MIT License - see the LICENSE file for details.

---

📌 Features

• 🔍 Detects phishing URLs using trained machine learning models.
• 🧠 Utilizes advanced URL feature extraction techniques.
• ⚙️ Simple, intuitive, and responsive web interface.
• 📊 Displays prediction results and confidence score.
• 🛠️ Built with Python Flask/Django and integrated with HTML/CSS/JS.

---

🛠️ Tech Stack

• Frontend: HTML, CSS, JavaScript
• Backend: Python, Flask
• Machine Learning: Pandas, NumPy
• Utilities: Joblib

---