Phishing emails that imitate trusted organizations remain a major threat to everyday email users. This project focuses on building a prototype Outlook add-in designed to detect and defend against spoofed emails that appear to come from the University of Connecticut (UConn). The system enhances the existing email experience by adding an intelligent layer of protection that helps users identify deceptive messages before interacting with them. Our approach combines machine learning with email authentication techniques. First, the system analyzes visible components of an email, such as the sender name, subject, and message content in order to determine whether it appears “UConn-like.” If an email matches these patterns, it is then verified using metadata and authentication checks, including mechanisms like SPF and DKIM, to confirm whether the sender is legitimate. Based on this two-step process, emails are classified as safe, suspicious, or non-relevant, and users are provided with clear feedback directly within the Outlook interface. By integrating detection and verification into a single workflow, this project aims to reduce successful phishing attempts and improve user awareness, offering a practical and scalable solution to a growing cybersecurity challenge.