Xin Zhang (Fudan University), Xiaohan Zhang (Fudan University), Zhichen Liu (Fudan University), Bo Zhao (Fudan University), Zhemin Yang (Fudan University), Min Yang (Fudan University)

Fingerprint-based authentication (FpAuth) is increasingly utilized by Android apps, particularly in highly sensitive scenarios such as account login and payment, as it can provide a convenient method for verifying user identity. However, the correct and secure use of Android fingerprint APIs (FpAPIs) in real-world mobile apps remains a challenge due to their complex and evolving nature.

This paper presents the first systematic empirical analysis of FpAPI misuses in Android apps from the perspective of the FpAuth lifecycle. First, we develop specialized tools to identify and analyze apps employing FpAPIs, examining their characteristics. Then we define the threat models and categorize four prevalent types of FpAPI misuses through a detailed lifecycle analysis in practical settings. Finally, we develop tools to automatically detect these misuse types in 1,333 apps that use FpAuth and find alarming results: 97.15% of them are vulnerable to at least one type of misuse, with 18.83% susceptible to all identified misuse types. The consequences of such misuses are significant, including unauthorized data access, account compromise, and even financial loss, impacting a broad user base. We have responsibly reported these vulnerabilities, resulting in the issuance of 184 CVE IDs and 19 China National Vulnerability Database (CNVD) IDs, as well as acknowledgment from 15 vendors. We hope this work can raise awareness and emphasize the importance of proper usage of FpAPIs.

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Cellular Metasploit

Dr. Yongdae Kim, Director, KAIST Chair Professor, Electrical Engineering and GSIS, KAIST

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MineShark: Cryptomining Traffic Detection at Scale

Shaoke Xi (Zhejiang University), Tianyi Fu (Zhejiang University), Kai Bu (Zhejiang University), Chunling Yang (Zhejiang University), Zhihua Chang (Zhejiang University), Wenzhi Chen (Zhejiang University), Zhou Ma (Zhejiang University), Chongjie Chen (HANG ZHOU CITY BRAIN CO., LTD), Yongsheng Shen (HANG ZHOU CITY BRAIN CO., LTD), Kui Ren (Zhejiang University)

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BumbleBee: Secure Two-party Inference Framework for Large Transformers

Wen-jie Lu (Ant Group), Zhicong Huang (Ant Group), Zhen Gu (Alibaba Group), Jingyu Li (Ant Group & Zhejiang University), Jian Liu (Zhejiang University), Cheng Hong (Ant Group), Kui Ren (Zhejiang University), Tao Wei (Ant Group), WenGuang Chen (Ant Group)

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Moneta: Ex-Vivo GPU Driver Fuzzing by Recalling In-Vivo Execution...

Joonkyo Jung (Department of Computer Science, Yonsei University), Jisoo Jang (Department of Computer Science, Yonsei University), Yongwan Jo (Department of Computer Science, Yonsei University), Jonas Vinck (DistriNet, KU Leuven), Alexios Voulimeneas (CYS, TU Delft), Stijn Volckaert (DistriNet, KU Leuven), Dokyung Song (Department of Computer Science, Yonsei University)

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