MiniScope: Automated UI Exploration and Privacy Inconsistency Detection of MiniApps via Two-phase Iterative Hybrid Analysis
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arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866929625890816000 |
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| author | Wang, Shenao Li, Yuekang Wang, Kailong Liu, Yi Li, Hui Liu, Yang Wang, Haoyu |
| author_facet | Wang, Shenao Li, Yuekang Wang, Kailong Liu, Yi Li, Hui Liu, Yang Wang, Haoyu |
| contents | The advent of MiniApps, operating within larger SuperApps, has revolutionized user experiences by offering a wide range of services without the need for individual app downloads. However, this convenience has raised significant privacy concerns, as these MiniApps often require access to sensitive data, potentially leading to privacy violations. Despite existing privacy regulations and platform guidelines, there is a lack of effective mechanisms to safeguard user privacy fully. To address this critical gap, we introduce MiniScope, a novel two-phase hybrid analysis approach, specifically designed for the MiniApp environment. This approach overcomes the limitations of existing static analysis techniques by incorporating UI transition states analysis, cross-package callback control flow resolution, and automated iterative UI exploration. This allows for a comprehensive understanding of MiniApps' privacy practices, addressing the unique challenges of sub-package loading and event-driven callbacks. Our empirical evaluation of over 120K MiniApps using MiniScope demonstrates its effectiveness in identifying privacy inconsistencies. The results reveal significant issues, with 5.7% of MiniApps over-collecting private data and 33.4% overclaiming data collection. We have responsibly disclosed our findings to 2,282 developers, receiving 44 acknowledgments. These findings emphasize the urgent need for more precise privacy monitoring systems and highlight the responsibility of SuperApp operators to enforce stricter privacy measures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_03218 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MiniScope: Automated UI Exploration and Privacy Inconsistency Detection of MiniApps via Two-phase Iterative Hybrid Analysis Wang, Shenao Li, Yuekang Wang, Kailong Liu, Yi Li, Hui Liu, Yang Wang, Haoyu Cryptography and Security Software Engineering The advent of MiniApps, operating within larger SuperApps, has revolutionized user experiences by offering a wide range of services without the need for individual app downloads. However, this convenience has raised significant privacy concerns, as these MiniApps often require access to sensitive data, potentially leading to privacy violations. Despite existing privacy regulations and platform guidelines, there is a lack of effective mechanisms to safeguard user privacy fully. To address this critical gap, we introduce MiniScope, a novel two-phase hybrid analysis approach, specifically designed for the MiniApp environment. This approach overcomes the limitations of existing static analysis techniques by incorporating UI transition states analysis, cross-package callback control flow resolution, and automated iterative UI exploration. This allows for a comprehensive understanding of MiniApps' privacy practices, addressing the unique challenges of sub-package loading and event-driven callbacks. Our empirical evaluation of over 120K MiniApps using MiniScope demonstrates its effectiveness in identifying privacy inconsistencies. The results reveal significant issues, with 5.7% of MiniApps over-collecting private data and 33.4% overclaiming data collection. We have responsibly disclosed our findings to 2,282 developers, receiving 44 acknowledgments. These findings emphasize the urgent need for more precise privacy monitoring systems and highlight the responsibility of SuperApp operators to enforce stricter privacy measures. |
| title | MiniScope: Automated UI Exploration and Privacy Inconsistency Detection of MiniApps via Two-phase Iterative Hybrid Analysis |
| topic | Cryptography and Security Software Engineering |
| url | https://arxiv.org/abs/2401.03218 |