Sohom Datta (North Carolina State University), Michalis Diamantaris (Technical University of Crete), Ahsan Zafar (North Carolina State University), Junhua Su (North Carolina State University), Anupam Das (North Carolina State University), Jason Polakis (University of Illinois Chicago), Alexandros Kapravelos (North Carolina State University)

WebViews are a prevalent method of embedding web-based content in Android apps. While they offer functionality similar to that of browsers and execute in an isolated context, apps can directly interfere with WebViews by dynamically injecting JavaScript code at runtime. While prior work has extensively analyzed apps' Java code, existing frameworks have limited visibility of the JavaScript code being executed inside WebViews. Consequently, there is limited understanding of the behaviors and characteristics of the scripts executed within WebViews, and whether privacy violations occur.

To address this gap, we propose WebViewTracer, a framework designed to dynamically analyze the execution of JavaScript code within WebViews at runtime. Our system combines within-WebView JavaScript execution traces with Java method-call information to also capture the information exchange occurring between Java SDKs and web scripts. We leverage WebViewTracer to perform the first large-scale, dynamic analysis of privacy-violating behaviors inside WebViews, on a dataset of 10K Android apps. We detect 4,597 apps that load WebViews, and find that over 69% of them inject sensitive and tracking-related information that is typically inaccessible to JavaScript code into WebViews. This includes identifiers like the Advertising ID and Android build ID. Crucially, 90% of those apps use web-based APIs to exfiltrate this information to third-party servers. We also uncover concrete evidence of common web fingerprinting techniques being used by JavaScript code inside WebViews, which can supplement their tracking information. We observe that the dynamic properties of WebViews are being actively leveraged for sensitive information diffusion across multiple actors in the mobile tracking ecosystem, demonstrating the privacy risks posed by Android WebViews. By shedding light on these ongoing privacy violations, our study seeks to prompt additional scrutiny from platform stakeholders on the use of embedded web technologies and highlights the need for additional safeguards.

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Chenxu Wang (Southern University of Science and Technology (SUSTech) and The Hong Kong Polytechnic University), Junjie Huang (Southern University of Science and Technology (SUSTech)), Yujun Liang (Southern University of Science and Technology (SUSTech)), Xuanyao Peng (Southern University of Science and Technology (SUSTech) and University of Chinese Academy of Sciences), Yuqun Zhang (Southern University of Science…

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Nuno Sabino (Carnegie Mellon University, Instituto Superior Técnico, Universidade de Lisboa, and Instituto de Telecomunicações), Darion Cassel (Carnegie Mellon University), Rui Abreu (Universidade do Porto, INESC-ID), Pedro Adão (Instituto Superior Técnico, Universidade de Lisboa, and Instituto de Telecomunicações), Lujo Bauer (Carnegie Mellon University), Limin Jia (Carnegie Mellon University)

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XiangFan Wu (Ocean University of China; QI-ANXIN Technology Research Institute), Lingyun Ying (QI-ANXIN Technology Research Institute), Guoqiang Chen (QI-ANXIN Technology Research Institute), Yacong Gu (Tsinghua University; Tsinghua University-QI-ANXIN Group JCNS), Haipeng Qu (Department of Computer Science and Technology, Ocean University of China)

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