A.Sushmitha, P. Akhila, D. Manasa, B. Pavani, S. Anusha 02 06 Phishing is an internet scam in which an attacker sends out fake messages that look to come from a trusted source A URL or file will be included in the mail which when clicked will steal personal information or infect a computer with a virus Traditionally phishing attempts were carried out through widescale spam campaigns that targeted broad groups of people indiscriminately The goal was to get as many people to click on a link or open an infected file as possible There are various approaches to detect this type of attack One of the approaches is machine learning The URLs received by the user will be given input to the machine learning model then the algorithm will process the input and display the output whether it is phishing or legitimate There are various ML algorithms like SVM Neural Networks Random Forest Decision Tree XG boost etc that can be used to classify these URLs The proposed approach deals with the Random Forest Decision Tree classifiers The proposed approach effectively classified the Phishing and Legitimate URLs with an accuracy of 870 and 824 for Random Forest and decision tree classifiers respectively Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026