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USENIX Security2023Top-tier venue

One Size Does Not Fit All: Uncovering and Exploiting Cross Platform Discrepant APIs in WeChat

Chao Wang, Yue Zhang, Zhiqiang Lin

2023Year
10Top-tier citations

Abstract

The past few years have witnessed a boom of mobile super apps, which are the apps offering multiple services such as e-commerce, e-learning, and e-government via miniapps executed inside. While originally designed for mobile platforms, super apps such as WeChat have also been made available on desktop platforms such as Windows. However, when running on desktop platforms, WeChat experiences differences in some behaviors, which presents opportunities for attacks (e.g., platform fingerprinting attacks). This paper thus aims to systematically identify the potential discrepancies in the APIs of WeChat across platforms and demonstrate how these differences can be exploited by remote attackers or local malicious miniapps. To this end, we present APIDIFF, an automatic tool that generates test cases for each API and identifies execution discrepancies. With APIDIFF, we have identified three sets of discrepant APIs that exhibit existence (109), permission (17), and output (22) discrepancies across platforms and devices, and provided concrete examples of their exploitation. We have responsibly disclosed these vulnerabilities to Tencent and received bug bounties for our findings. These vulnerabilities were ranked as high-severity and some have already been patched.

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