Penny for Your Prompts: A Measurement Study of Contextual Leakage in AI Chat Platforms

A measurement study examining 42 general-purpose and specialized AI chatbot platforms (spanning health, legal, and education domains) demonstrates that standard web tracking technologies, including analytics, advertising, and session replay scripts, operate silently alongside conversational interfaces, creating an underexamined pathway for sensitive user prompts to leak to third parties.

This development matters because it demonstrates that privacy vulnerabilities in AI deployments often stem from routine web application architecture rather than model-level failures. Organizations interacting with or hosting AI interfaces face severe regulatory, competitive, and reputational exposure if proprietary or confidential inquiries are harvested by third-party tracking networks. Consequently, data governance frameworks must account for client-side exfiltration vectors alongside backend API security.

AI chatbot platforms routinely collect intimate and sensitive user information under an assumed expectation of user privacy.

Forward consideration, not a verified fact.