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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Crosstalk-induced Side Channel Threats in Multi-Tenant NISQ Computers

Ruixuan Li (Choudhury), Chaithanya Naik Mude (University of Wisconsin-Madison), Sanjay Das (The University of Texas at Dallas), Preetham Chandra Tikkireddi (University of Wisconsin-Madison), Swamit Tannu (University of Wisconsin, Madison), Kanad Basu (University of Texas at Dallas)

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Sian Kim (Ewha Womans University), Seyed Mohammad Mehdi Mirnajafizadeh (Wayne State University), Bara Kim (Korea University), Rhongho Jang (Wayne State University), DaeHun Nyang (Ewha Womans University)

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LLM-xApp: A Large Language Model Empowered Radio Resource Management...

Xingqi Wu (University of Michigan-Dearborn), Junaid Farooq (University of Michigan-Dearborn), Yuhui Wang (University of Michigan-Dearborn), Juntao Chen (Fordham University)

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