Expecting (Targeted Ads)? Network Analysis of User Health Data Leakage in Fertility Tracking Apps

2026-06-24

AI Summary

This study systematically investigates the technical mechanisms and privacy risks associated with the leakage of users’ reproductive health data from fertility-tracking applications through advertising channels. By performing measurement analysis on TLS-decrypted network traffic from 20 Android apps under standardized user interactions—augmented with network monitoring, man-in-the-middle proxying, and contextual ad URL parsing—the research uncovers, for the first time, concrete pathways through which sensitive health information is explicitly or implicitly exposed via highly targeted advertising interfaces. Explicit leakage of sensitive data was identified in five apps, while others, despite integrating ad SDKs, demonstrated effective privacy-preserving practices. These findings highlight significant disparities in developer implementation strategies and provide empirical evidence to inform user choices regarding app selection and data privacy.

Abstract

While human factors in the privacy of fertility tracking apps -- health trackers that record user's menstrual or pregnancy data -- has been the subject of extensive study, little attention has been paid to the technical aspects of apps' data handling practices. We conduct a network-based measurement study of a corpus of 20 Android fertility tracking apps from the Google Play Store, focusing on how user data is shared with third party advertising services. After systematizing app features, we conduct a series of standardized user interactions across all apps in an environment that records TLS-stripped network traffic. In a subset of apps (n=5) we identify explicit leakage of user health data as well implicit leakage through highly targeted contextual advertising URL's. Equally importantly, we observe additional apps that use an ad-based monetization model without apparent leakage of user data, as well as several apps the interact only minimally with ad services. These findings provide technical grounding for widespread user concerns, but also underscore the importance of consumer choice in the privacy implications of app-based fertility tracking.

Problem

• fertility tracking apps
• health data leakage
• third-party advertising
• user privacy
• data sharing

Innovation

• network traffic analysis
• health data leakage
• fertility tracking apps
• contextual advertising
• privacy measurement