How to Build a Python-Based AI Phishing URL Detector Using ML and LLMs

A technical guide published on DEV Community outlines how to build a phishing URL detector in Python using feature engineering and machine learning. The approach identifies structural patterns common to malicious URLs, such as excessive dots, high domain entropy, suspicious keywords, and IP-based hostnames. A gradient boosting classifier trained on PhishTank and Tranco datasets forms the core detection layer. An additional language model escalation step is proposed to handle ambiguous cases that the classifier cannot confidently resolve. The system is designed not for perfect accuracy but as a fast, reliable security layer that flags suspicious URLs before users click them.