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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Eduardo Chielle (New York University Abu Dhabi), Michail Maniatakos (New York University Abu Dhabi)

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The Road to Trust: Building Enclaves within Confidential VMs

Wenhao Wang (Key Laboratory of Cyberspace Security Defense, Institute of Information Engineering, CAS), Linke Song (Key Laboratory of Cyberspace Security Defense, Institute of Information Engineering, CAS), Benshan Mei (Key Laboratory of Cyberspace Security Defense, Institute of Information Engineering, CAS), Shuang Liu (Ant Group), Shijun Zhao (Key Laboratory of Cyberspace Security Defense, Institute of Information Engineering,…

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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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YuraScanner: Leveraging LLMs for Task-driven Web App Scanning

Aleksei Stafeev (CISPA Helmholtz Center for Information Security), Tim Recktenwald (CISPA Helmholtz Center for Information Security), Gianluca De Stefano (CISPA Helmholtz Center for Information Security), Soheil Khodayari (CISPA Helmholtz Center for Information Security), Giancarlo Pellegrino (CISPA Helmholtz Center for Information Security)

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