Elizabeth Lin (North Carolina State University), Igibek Koishybayev (North Carolina State University), Trevor Dunlap (North Carolina State University), William Enck (North Carolina State University), Alexandros Kapravelos (North Carolina State University)

With the rise in threats against the software supply chain, developer integrated development environments (IDEs) present an attractive target for attackers. For example, researchers have found extensions for Visual Studio Code (VS Code) that start web servers and can be exploited via JavaScript executing in a web browser on the developer's host. This paper seeks to systematically understand the landscape of vulnerabilities in VS Code's extension marketplace. We identify a set of four sources of untrusted input and three code targets that can be used for code injection and file integrity attacks and use them to design taint analysis rules in CodeQL. We then perform an ecosystem-level analysis of the VS Code extension marketplace, studying 25,402 extensions that contain code. Our results show that while vulnerabilities are not pervasive, they exist and impact millions of users. Specifically, we find 21 extensions with verified proof of concept exploits of code injection attacks impacting a total of over 6 million installations. Through this study, we demonstrate the need for greater attention to the security of IDE extensions.

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MOCK: Optimizing Kernel Fuzzing Mutation with Context-aware Dependency

Jiacheng Xu (Zhejiang University), Xuhong Zhang (Zhejiang University), Shouling Ji (Zhejiang University), Yuan Tian (UCLA), Binbin Zhao (Georgia Institute of Technology), Qinying Wang (Zhejiang University), Peng Cheng (Zhejiang University), Jiming Chen (Zhejiang University)

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A Security and Usability Analysis of Local Attacks Against...

Tarun Kumar Yadav (Brigham Young University), Kent Seamons (Brigham Young University)

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Facilitating Threat Modeling by Leveraging Large Language Models

Isra Elsharef, Zhen Zeng (University of Wisconsin-Milwaukee), Zhongshu Gu (IBM Research)

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Enhance Stealthiness and Transferability of Adversarial Attacks with Class...

Hui Xia (Ocean University of China), Rui Zhang (Ocean University of China), Zi Kang (Ocean University of China), Shuliang Jiang (Ocean University of China), Shuo Xu (Ocean University of China)

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