Yunpeng Tian (Huazhong University of Science and Technology), Feng Dong (Huazhong University of Science and Technology), Haoyi Liu (Huazhong University of Science and Technology), Meng Xu (University of Waterloo), Zhiniang Peng (Huazhong University of Science and Technology; Sangfor Technologies Inc.), Zesen Ye (Sangfor Technologies Inc.), Shenghui Li (Huazhong University of Science and Technology), Xiapu Luo (The Hong Kong Polytechnic University), Haoyu Wang (Huazhong University of Science and Technology)

Microsoft Office is a comprehensive suite of productivity tools and Object Linking & Embedding (OLE) is a specification that standardizes the linking and embedding of a diverse set of objects across different applications.OLE facilitates data interchange and streamlines user experience when dealing with composite documents (e.g., an embedded Excel sheet in a Word document). However, inherent security weaknesses within the design of OLE present risks, as the design of OLE inherently blurs the trust boundary between first-party and third-party code, which may lead to unintended library loading and parsing vulnerabilities which could be exploited by malicious actors. Addressing this issue, this paper introduces OLExplore, a novel tool designed for security assessment of Office OLE objects.With an in-depth examination of historical OLE vulnerabilities, we have identified three key categories of vulnerabilities and subjected them to dynamic analysis and verification. Our evaluation of various Windows operating system versions has led to the discovery of 26 confirmed vulnerabilities, with 17 assigned CVE numbers that all have remote code execution potential.

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DiStefano: Decentralized Infrastructure for Sharing Trusted Encrypted Facts and...

Sofia Celi (Brave Software), Alex Davidson (NOVA LINCS & Universidade NOVA de Lisboa), Hamed Haddadi (Imperial College London & Brave Software), Gonçalo Pestana (Hashmatter), Joe Rowell (Information Security Group, Royal Holloway, University of London)

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Towards LLM-Assisted Vulnerability Detection and Repair for Open-Source 5G...

Rupam Patir (University at Buffalo), Qiqing Huang (University at Buffalo), Keyan Guo (University at Buffalo), Wanda Guo (Texas A&M University), Guofei Gu (Texas A&M University), Haipeng Cai (University at Buffalo), Hongxin Hu (University at Buffalo)

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Siniel: Distributed Privacy-Preserving zkSNARK

Yunbo Yang (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Yuejia Cheng (Shanghai DeCareer Consulting Co., Ltd), Kailun Wang (Beijing Jiaotong University), Xiaoguo Li (College of Computer Science, Chongqing University), Jianfei Sun (School of Computing and Information Systems, Singapore Management University), Jiachen Shen (Shanghai Key Laboratory of Trustworthy Computing, East China Normal…

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SketchFeature: High-Quality Per-Flow Feature Extractor Towards Security-Aware Data Plane

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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