The Hartnell Phishing team developed a serverless phishing-analysis pipeline that converts labeled email reports into audience-specific security awareness materials and a browser-based dashboard. Building on AWS infrastructure provided by the Hartnell IT team—Amazon S3 (cloud storage) and AWS Lambda (serverless compute)—the summer camp team built a Python classifier that categorizes reported phishing messages into twenty higher-education-specific threat types using a rule-based engine, recognizing patterns like Canvas credential phishing, financial-aid scams, fake internships, and MFA reset lures. After classification, the Lambda calculates deterministic insights from category statistics—leading threat, second category, uncategorized percentage, and a recommendation to prioritize awareness for the top pattern—then renders four audience-specific HTML drafts and a CSV statistics file, writes immutable per-run artifacts to a drafts bucket on Amazon S3, and publishes a completion manifest so the dashboard loads the newest results automatically. The dashboard uses Chart.js to visualize category metrics directly in the browser, and the entire pipeline runs locally within the institution’s AWS account with no email content leaving for external analysis, giving Hartnell College IT staff a faster, auditable, and cost-effective way to identify monthly phishing trends, generate executive reports, and produce targeted security alerts for students, faculty, and staff—ultimately saving hours of manual effort each month and enabling proactive communication about the specific threats their campus community faces.