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| Content Provider | ACM Digital Library |
|---|---|
| Author | Li, Bodong Yang, Wenbo Li, Juanru Wang, Hui Zhang, Yuanyuan Liu, Hui Gu, Dawu |
| Abstract | Enforcing security on various implementations of OAuth in Android apps should consider a wide range of issues comprehensively. OAuth implementations in Android apps differ from the recommended specification due to the provider and platform factors, and the varied implementations often become vulnerable. Current vulnerability assessments on these OAuth implementations are ad hoc and lack a systematic manner. As a result, insecure OAuth implementations are still widely used and the situation is far from optimistic in many mobile app ecosystems. To address this problem, we propose a systematic vulnerability assessment framework for OAuth implementations on Android platform. Different from traditional OAuth security analyses that are experiential with a restrictive three-party model, our proposed framework utilizes an systematic security assessing methodology that adopts a five-party, three-stage model to detect typical vulnerabilities of popular OAuth implementations in Android apps. Based on this framework, a comprehensive investigation on vulnerable OAuth implementations is conducted at the level of an entire mobile app ecosystem. The investigation studies the Chinese mainland mobile app markets (e.g., Baidu App Store, Tencent, Anzhi) that covers 15 mainstream OAuth service providers. Top 100 relevant relying party apps (RP apps) are thoroughly assessed to detect vulnerable OAuth implementations, and we further perform an empirical study of over 4,000 apps to validate how frequently developers misuse the OAuth protocol. The results demonstrate that 86.2% of the apps incorporating OAuth services are vulnerable, and this ratio of Chinese mainland Android app market is much higher than that (58.7%) of Google Play. |
| Starting Page | 61 |
| Ending Page | 70 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450336826 |
| DOI | 10.1145/2818000.2818024 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-12-07 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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