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

• URL: http://arxiv.org/abs/2503.15238v1
• Date: Wed, 19 Mar 2025 14:15:02 GMT
• Title: Your Signal, Their Data: An Empirical Privacy Analysis of Wireless-scanning SDKs in Android
• Authors: Aniketh Girish, Joel Reardon, Juan Tapiador, Srdjan Matic, Narseo Vallina-Rodriguez,
• Abstract summary: Mobile apps frequently use Bluetooth Low Energy (BLE) and WiFi scanning permissions to discover nearby devices.<n>Wireless interfaces also serve as a covert proxy for geolocation data, enabling continuous user tracking and profiling.<n>We conduct the first systematic analysis of 52 wireless-scanning SDKs, revealing their data collection practices and privacy risks.
• Score: 3.830984415546144
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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