MiniScope: Automated UI Exploration and Privacy Inconsistency Detection of MiniApps via Two-phase Iterative Hybrid Analysis
Shenao Wang, Yuekang Li, Kailong Wang, Yi Liu, Hui Li, Yang Liu, Haoyu, Wang

TL;DR
MiniScope is a two-phase hybrid analysis tool that detects privacy inconsistencies in MiniApps within SuperApps, revealing significant privacy violations and emphasizing the need for better privacy enforcement.
Contribution
It introduces a novel two-phase hybrid analysis approach that overcomes static analysis limitations by incorporating UI transition analysis and automated exploration for MiniApps.
Findings
5.7% of MiniApps over-collect private data
33.4% overclaim data collection
Analyzed over 120,000 MiniApps with effective results
Abstract
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…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Advanced Data Storage Technologies · Caching and Content Delivery
