Execution trace data from: Cross-boundary mobile tracking: exploring Java-to-JavaScript information diffusion in WebViews
Data files
Sep 18, 2025 version files 76.10 GB
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log_apr_24_2025.tar.gz
76.10 GB
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README.md
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Abstract
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 almost 4,600 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 of 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 safeguard. This dataset contains the execution traces of all apps successfully executed in our dataset.
This dataset contains a compressed archive (log_apr_24_2025.tar.gz) of all of the execution traces obtained during our large-scale dynamic analysis of Android Apps as part of our NDSS 2026 paper "Cross-Boundary Mobile Tracking: Exploring Java-to-JavaScript Information Diffusion in WebViews". The dataset contains the Frida logs generated by Java code invoking WebView-specific functions and VisibleV8 logs of JavaScript code execution inside the webview loaded by our dataset of 10K apps. Further details regarding the files are provided in our artifact appendix.
Note: The compressed size of the tar file is approximately 75GB, which should expand to approximately 500 GB of data when uncompressed.
