Runze Zhang (Georgia Institute of Technology), Mingxuan Yao (Georgia Institute of Technology), Haichuan Xu (Georgia Institute of Technology), Omar Alrawi (Georgia Institute of Technology), Jeman Park (Kyung Hee University), Brendan Saltaformaggio (Georgia Institute of Technology)

For decades, law enforcement and commercial entities have attempted botnet takedowns with mixed success. These efforts, relying on DNS sink-holing or seizing C&C infrastructure, require months of preparation and often omit the cleanup of left-over infected machines. This allows botnet operators to push updates to the bots and re-establish their control. In this paper, we expand the goal of malware takedowns to include the covert and timely removal of frontend bots from infected devices. Specifically, this work proposes seizing the malware's built-in update mechanism to distribute crafted remediation payloads. Our research aims to enable this necessary but challenging remediation step after obtaining legal permission. We developed ECHO, an automated malware forensics pipeline that extracts payload deployment routines and generates remediation payloads to disable or remove the frontend bots on infected devices. Our study of 702 Android malware shows that 523 malware can be remediated via ECHO's takedown approach, ranging from covertly warning users about malware infection to uninstalling the malware.

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Scale-MIA: A Scalable Model Inversion Attack against Secure Federated...

Shanghao Shi (Virginia Tech), Ning Wang (University of South Florida), Yang Xiao (University of Kentucky), Chaoyu Zhang (Virginia Tech), Yi Shi (Virginia Tech), Y. Thomas Hou (Virginia Polytechnic Institute and State University), Wenjing Lou (Virginia Polytechnic Institute and State University)

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Compiled Models, Built-In Exploits: Uncovering Pervasive Bit-Flip Attack Surfaces...

Yanzuo Chen (The Hong Kong University of Science and Technology), Zhibo Liu (The Hong Kong University of Science and Technology), Yuanyuan Yuan (The Hong Kong University of Science and Technology), Sihang Hu (Huawei Technologies), Tianxiang Li (Huawei Technologies), Shuai Wang (The Hong Kong University of Science and Technology)

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HADES Attack: Understanding and Evaluating Manipulation Risks of Email...

Ruixuan Li (Tsinghua University), Chaoyi Lu (Tsinghua University), Baojun Liu (Tsinghua University;Zhongguancun Laboratory), Yunyi Zhang (Tsinghua University), Geng Hong (Fudan University), Haixin Duan (Tsinghua University;Zhongguancun Laboratory), Yanzhong Lin (Coremail Technology Co. Ltd), Qingfeng Pan (Coremail Technology Co. Ltd), Min Yang (Fudan University), Jun Shao (Zhejiang Gongshang University)

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