PhishGuard

Real-time phishing detection: blocklist, domain analysis, NLP content scanning, and threat intelligence APIs.

This project is a machine learning–based phishing detection system designed to identify and prevent malicious websites in real time. The system consists of a Flask-based web application that serves as the backend, integrating a trained detection model, a database, and supporting logic for analysis. A browser extension acts as the primary user interface, continuously monitoring URLs visited by the user and sending them to the Flask backend for evaluation. The machine learning model analyzes features of each URL—such as structure, domain characteristics, and known phishing patterns—to classify it as either legitimate or suspicious. The system then returns a result to the browser extension, which alerts the user if a potential phishing threat is detected. This architecture enables lightweight client-side interaction while leveraging more powerful server-side processing for accurate detection.