PrivPRISM: Automatically Detecting Discrepancies Between Google Play Data Safety Declarations and Developer Privacy Policies
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Abstract (arXiv)
End-users seldom read verbose privacy policies, leading app stores like Google Play to mandate simplified data safety declarations as a user-friendly alternative. However, these self-declared disclosures often contradict the full privacy policies, deceiving users about actual data practices and violating regulatory requirements for consistency. To address this, we introduce PrivPRISM, a robust framework that combines encoder and decoder language models to systematically extract and compare fine-grained data practices from privacy policies and to compare against data safety declarations, enabling scalable detection of non-compliance. Evaluating 7,770 popular mobile games uncovers discrepancies in nearly 53% of cases, rising to 61% among 1,711 widely used generic apps. Additionally, static code analysis reveals possible under-disclosures, with privacy policies disclosing just 66.8% of potential accesses to sensitive data like location and financial information, versus only 36.4% in data safety declarations of mobile games. Our findings expose systemic issues, including widespread reuse of generic privacy policies, vague / contradictory statements, and hidden risks in high-profile apps with 100M+ downloads, underscoring the urgent need for automated enforcement to protect platform integrity and for end-users to be vigilant about sensitive data they disclose via popular apps.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 15 of its 43 references that are in the map. First posted on arXiv 10 Mar 2026.
Builds on
15 of 43 references.
References · 15
- 2024The Llama 3 Herd of Modelscited by 14,192
- 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
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- 2024CLEAR: Towards Contextual LLM-Empowered Privacy Policy Analysis and Risk Generation for Large Language Model Applicationscited by 33
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- 2018The Privacy Policy Landscape After the GDPRcited by 18
- 2023PolicyGPT: Automated Analysis of Privacy Policies with Large Language Modelscited by 16
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- 2022PoliGraph: Automated Privacy Policy Analysis using Knowledge Graphs (Journal Version)cited by 10
- 2023Unpacking Privacy Labels: A Measurement and Developer Perspective on Google's Data Safety Sectioncited by 6
- 2025"You don't need a university degree to comprehend data protection this way": LLM-Powered Interactive Privacy Policy Assessmentcited by 5
3 more
- 2023Automating Governing Knowledge Commons and Contextual Integrity (GKC-CI) Privacy Policy Annotations with Large Language Modelscited by 3
- 2024Entailment-Driven Privacy Policy Classification with LLMscited by 2
- 2024Do Android App Developers Accurately Report Collection of Privacy-Related Data?cited by 1
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Citing papers per year: 2026: 1.
1 paper.