Hao Zhou (The Hong Kong Polytechnic University), Shuohan Wu (The Hong Kong Polytechnic University), Chenxiong Qian (University of Hong Kong), Xiapu Luo (The Hong Kong Polytechnic University), Haipeng Cai (Washington State University), Chao Zhang (Tsinghua University)

Overlay is a notable user interface feature in the Android system, which allows an app to draw over other apps' windows. While overlay enhances user experience and allows concurrent app interaction, it has been extensively abused for malicious purposes, such as "tapjacking", leading to so-called overlay attacks. In order to combat this threat, Google introduced a dedicated window flag SYSTEM_FLAG_HIDE_NON_SYSTEM_OVERLAY_WINDOWS to protect critical system apps' windows against overlay attacks. Unfortunately, the adequacy of such protection in the Android system remains unstudied, with a noticeable absence of clear usage guidelines.

To bridge the gap, in this paper, we conduct the first systematic study on the unprotected windows of system apps against overlay attacks. We propose a comprehensive guideline and then design and develop a new tool named OverlayChecker to identify the missing protections in Android system apps. To verify the uncovered issues, we also design and create Proof-of-Concept apps. After applying OverlayChecker to 8 commercial Android systems on 4 recently released Android versions, we totally discovered 49 vulnerable system apps' windows. We reported our findings to the mobile vendors, including Google, Samsung, Vivo, Xiaomi, and Honor. At the time of writing, 15 of them have been confirmed. 5 CVEs have been assigned, and 3 of them are rated high severity. We also received bug bounty rewards from these mobile vendors.

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Fannv He (National Computer Network Intrusion Protection Center, University of Chinese Academy of Sciences, China), Yan Jia (DISSec, College of Cyber Science, Nankai University, China), Jiayu Zhao (National Computer Network Intrusion Protection Center, University of Chinese Academy of Sciences, China), Yue Fang (National Computer Network Intrusion Protection Center, University of Chinese Academy of Sciences, China),…

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Linkang Du (Zhejiang University), Zheng Zhu (Zhejiang University), Min Chen (CISPA Helmholtz Center for Information Security), Shouling Ji (Zhejiang University), Peng Cheng (Zhejiang University), Jiming Chen (Zhejiang University), Zhikun Zhang (Stanford University)

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Ryo Suzuki (Keio University), Takami Sato (University of California, Irvine), Yuki Hayakawa, Kazuma Ikeda, Ozora Sako, Rokuto Nagata (Keio University), Qi Alfred Chen (University of California, Irvine), Kentaro Yoshioka (Keio University)

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Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

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Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)