Your Signal, Their Data: An Empirical Privacy Analysis of Wireless-scanning SDKs in Android

Mobile apps frequently use Bluetooth Low Energy (BLE) and WiFi scanning permissions to discover nearby devices like peripherals and connect to WiFi Access Points (APs). However, wireless interfaces also serve as a covert proxy for geolocation data, enabling continuous user tracking and profiling. This includes technologies like BLE beacons, which are BLE devices broadcasting unique identifiers to determine devices' indoor physical locations; such beacons are easily found in shopping centres. Despite the widespread use of wireless scanning APIs and their potential for privacy abuse, the interplay between commercial mobile SDKs with wireless sensing and beaconing technologies remains largely unexplored. In this work, we conduct the first systematic analysis of 52 wireless-scanning SDKs, revealing their data collection practices and privacy risks. We develop a comprehensive analysis pipeline that enables us to detect beacon scanning capabilities, inject wireless events to trigger app behaviors, and monitor runtime execution on instrumented devices. Our findings show that 86% of apps integrating these SDKs collect at least one sensitive data type, including device and user identifiers such as AAID, email, along with GPS coordinates, WiFi and Bluetooth scan results. We uncover widespread SDK-to-SDK data sharing and evidence of ID bridging, where persistent and resettable identifiers are shared and synchronized within SDKs embedded in applications to potentially construct detailed mobility profiles, compromising user anonymity and enabling long-term tracking. We provide evidence of key actors engaging in these practices and conclude by proposing mitigation strategies such as stronger SDK sandboxing, stricter enforcement of platform policies, and improved transparency mechanisms to limit unauthorized tracking.

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Publication Details

Journal
Proceedings on Privacy Enhancing Technologies
Published
2025-05-19
DOI
https://doi.org/10.56553/popets-2025-0103
Citations
1
Primary Topic
Privacy, Security, and Data Protection
Type
article
Field-Weighted Citation Impact
4.20
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article

Your Signal, Their Data: An Empirical Privacy Analysis of Wireless-scanning SDKs in Android

Narseo Vallina-Rodríguez, Joel Reardon, Aniketh Girish, Juan Tapiador et al.
1 citations
Proceedings on Privacy Enhancing Technologies
Privacy, Security, and Data Protection
4.20
article

Your Signal, Their Data: An Empirical Privacy Analysis of Wireless-scanning SDKs in Android

Narseo Vallina-Rodríguez, Joel Reardon, Aniketh Girish, Juan Tapiador, Srdjan Matic
article en
1 citations

Abstract

Mobile apps frequently use Bluetooth Low Energy (BLE) and WiFi scanning permissions to discover nearby devices like peripherals and connect to WiFi Access Points (APs). However, wireless interfaces also serve as a covert proxy for geolocation data, enabling continuous user tracking and profiling. This includes technologies like BLE beacons, which are BLE devices broadcasting unique identifiers to determine devices' indoor physical locations; such beacons are easily found in shopping centres. Despite the widespread use of wireless scanning APIs and their potential for privacy abuse, the interplay between commercial mobile SDKs with wireless sensing and beaconing technologies remains largely unexplored. In this work, we conduct the first systematic analysis of 52 wireless-scanning SDKs, revealing their data collection practices and privacy risks. We develop a comprehensive analysis pipeline that enables us to detect beacon scanning capabilities, inject wireless events to trigger app behaviors, and monitor runtime execution on instrumented devices. Our findings show that 86% of apps integrating these SDKs collect at least one sensitive data type, including device and user identifiers such as AAID, email, along with GPS coordinates, WiFi and Bluetooth scan results. We uncover widespread SDK-to-SDK data sharing and evidence of ID bridging, where persistent and resettable identifiers are shared and synchronized within SDKs embedded in applications to potentially construct detailed mobility profiles, compromising user anonymity and enabling long-term tracking. We provide evidence of key actors engaging in these practices and conclude by proposing mitigation strategies such as stronger SDK sandboxing, stricter enforcement of platform policies, and improved transparency mechanisms to limit unauthorized tracking.

Proceedings on Privacy Enhancing TechnologiesVol. 2025(3)
University of Calgary (CA), IMDEA Networks (ES), IMDEA Software Institute (ES), Universidad Carlos III de Madrid (ES)
Openalex Percentile: Top 8%
Privacy, Security, and Data Protection
4.20
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