Fangming Gu (Institute of Information Engineering, Chinese Academy of Sciences), Qingli Guo (Institute of Information Engineering, Chinese Academy of Sciences), Jie Lu (Institute of Computing Technology, Chinese Academy of Sciences), Qinghe Xie (Institute of Information Engineering, Chinese Academy of Sciences), Beibei Zhao (Institute of Information Engineering, Chinese Academy of Sciences), Kangjie Lu (University of Minnesota), Hong Li (Institute of information engineering, Chinese Academy of Sciences), Xiaorui Gong (Institute of information engineering, Chinese Academy of Sciences)

The Windows operating system employs various inter-process communication (IPC) mechanisms, typically involving a privileged server and a less privileged client. However, scenarios exist where the client has higher privileges, such as a performance monitor running as a domain controller obtaining data from a domain member via IPC. In these cases, the server can be compromised and send crafted data to the client.
Despite the increase in Windows client applications, existing research has overlooked potential client-side vulnerabilities, which can be equally harmful. This paper introduces GLEIPNIR, the first vulnerability detection tool for Windows remote IPC clients. GLEIPNIR identifies client-side vulnerabilities by fuzzing IPC call return values and introduces a snapshot technology to enhance testing efficiency. Experiments on 76 client applications demonstrate that GLEIPNIR can identify 25 vulnerabilities within 7 days, resulting in 14 CVEs and a bounty of $36,000.

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Jung-Woo Chang (University of California, San Diego), Ke Sun (University of California, San Diego), Nasimeh Heydaribeni (University of California, San Diego), Seira Hidano (KDDI Research, Inc.), Xinyu Zhang (University of California, San Diego), Farinaz Koushanfar (University of California, San Diego)

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Characterizing the Impact of Audio Deepfakes in the Presence...

Magdalena Pasternak (University of Florida), Kevin Warren (University of Florida), Daniel Olszewski (University of Florida), Susan Nittrouer (University of Florida), Patrick Traynor (University of Florida), Kevin Butler (University of Florida)

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Diffence: Fencing Membership Privacy With Diffusion Models

Yuefeng Peng (University of Massachusetts Amherst), Ali Naseh (University of Massachusetts Amherst), Amir Houmansadr (University of Massachusetts Amherst)

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Onion Franking: Abuse Reports for Mix-Based Private Messaging

Matthew Gregoire (University of North Carolina at Chapel Hill), Margaret Pierce (University of North Carolina at Chapel Hill), Saba Eskandarian (University of North Carolina at Chapel Hill)

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