Zihao Jin (Microsoft Research and Tsinghua University), Shuo Chen (Microsoft Research), Yang Chen (Microsoft Research), Haixin Duan (Tsinghua University and Quancheng Laboratory), Jianjun Chen (Tsinghua University and Zhongguancun Laboratory), Jianping Wu (Tsinghua University)

The Electron platform represents a paradigm to develop modern desktop apps using HTML and JavaScript. Microsoft Teams, Visual Studio Code and other flagship products are examples of Electron apps. This new paradigm inherits the security challenges in web programming into the desktop-app realm, thus opens a new way for local-machine exploitation. We conducted a security study about real-world Electron apps, and discovered many vulnerabilities that are now confirmed by the app vendors. The conventional wisdom is to view these bugs as *sanitization errors*. Accordingly, secure programming requires programmers to explicitly enumerate all kinds of unexpected inputs to sanitize. We believe that secure programming should focus on specifying programmers' intentions as opposed to their non-intentions. We introduce a concept called *DOM-tree type*, which expresses the set of DOM trees that an app expects to see during execution, so an exploit will be caught as a type violation. With insights into the HTML standard and the Chromium engine, we build the DOM-tree type mechanism into the Electron platform. The evaluations show that the methodology is practical, and it secures all vulnerable apps that we found in the study.

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Zachary Depp, Halit Bugra Tulay, C. Emre Koksal (The Ohio State University)

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Wanlun Ma (Swinburne University of Technology), Derui Wang (CSIRO’s Data61), Ruoxi Sun (The University of Adelaide & CSIRO's Data61), Minhui Xue (CSIRO's Data61), Sheng Wen (Swinburne University of Technology), Yang Xiang (Digital Research & Innovation Capability Platform, Swinburne University of Technology)

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Jinseob Jeong (KAIST, Agency for Defense Development), Dongkwan Kim (Samsung SDS), Joonha Jang (KAIST), Juhwan Noh (KAIST), Changhun Song (KAIST), Yongdae Kim (KAIST)

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Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

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)