Why Choose This Project?

Phishing attacks are among the most common cybersecurity threats today. Users are often tricked into clicking malicious URLs that look like legitimate ones. This project offers an intelligent phishing detection system that identifies suspicious URLs using machine learning or rule-based techniques. It's an excellent real-world security solution and showcases how AI and security blend to protect users.

What You Get in This Project

• Fully working web application to detect phishing URLs

• Admin/User-friendly interface to input, scan, and view results

• Trained machine learning model or regex-based rule engine

• Database of known phishing and safe URLs

• Exportable scan logs and detection results

• Real-time prediction with alerts and suggestions

• Complete source code, database schema, and documentation

• Mobile and desktop responsive design

Technology Stack Used

How It Works (Workflow)

1. User Inputs URL
   User pastes a URL into the input field and clicks “Scan.”

2. Preprocessing
   The URL is broken into features like length, domain age, use of @, IP address, HTTPS, etc.

3. Detection Engine

   • Option A (ML-based): Trained classifier (Random Forest, SVM, etc.) predicts if the URL is phishing.

   • Option B (Rule-based): Uses heuristics (e.g., suspicious domain, use of misleading subdomains).

4. Result Display
   The app shows:

   • Risk Score

   • Reason for flagging

   • Safe/Phishing classification

   • Suggestions for user safety

5. Reporting
   Results can be downloaded or emailed to admins.