Prompt like a Butterfly, Sting like a Tracker: A Privacy Analysis of Web and Mobile Conversational AI Agents
In this paper, we present a systematic privacy analysis of the web and mobile deployments of nine prominent conversational AI services. Using a combination of static and dynamic analysis, we study the presence of third-party Advertising and Tracking Services (ATSes), characterize their data flows, and evaluate how consent choices, subscription tiers, and access-control mechanisms influence conversation exposure to third parties. We uncover privacy risks unique to conversational AI platforms: multiple providers disclose sensitive conversation-derived artifacts—including titles, prompts, and screenshots—to third parties, often alongside persistent user identifiers that enable user attribution. We also find that some providers publicly expose conversation permalinks without access controls, allowing trackers to read the entire conversation