This document summarizes Shreya Gopal Sundari's project on detecting phishing websites using machine learning techniques. The objectives are to collect a dataset of phishing and legitimate URLs, extract relevant features from the URLs, train machine learning models on the dataset, and evaluate the models' performance in classifying URLs as phishing or legitimate. Key steps include collecting 5000 phishing and 5000 legitimate URLs, extracting 17 features related to the URLs and websites, training models like decision trees, random forests, neural networks and support vector machines, and finding that XGBoost achieved the best accuracy. Potential next steps are developing a browser extension or GUI to classify new URLs.