Swipe Left for Identity Theft: An Analysis of User Data Privacy Risks on Location-based Dating Apps


Karel Dhondt, Victor Le Pochat, Yana Dimova, Wouter Joosen, and Stijn Volckaert, DistriNet, KU Leuven

This paper is currently under embargo, but the paper abstract is available now. The final paper PDF will be available on the first day of the conference.


Location-based dating (LBD) apps enable users to meet new people nearby and online by browsing others' profiles, which often contain very personal and sensitive data. We systematically analyze 15 LBD apps on the prevalence of privacy risks that can result in abuse by adversarial users who want to stalk, harass, or harm others. Through a systematic manual analysis of these apps, we assess which personal and sensitive data is shared with other users, both as (intended) data exposure and as inadvertent yet powerful leaks in API traffic that is otherwise hidden from a user, violating their mental model of what they share on LBD apps. We also show that 6 apps allow for pinpointing a victim's exact location, enabling physical threats to users' personal safety. All these data exposures and leaks—supported by easy account creation—enable targeted or large-scale, long-term, and stealthy profiling and tracking of LBD app users. While privacy policies acknowledge personal data processing, and a tension exists between app functionality and user privacy, significant data privacy risks remain. We recommend user control, data minimization, and API hardening as countermeasures to protect users' privacy.