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.

View More Papers

Enhancing Security in Third-Party Library Reuse – Comprehensive Detection...

Shangzhi Xu (The University of New South Wales), Jialiang Dong (The University of New South Wales), Weiting Cai (Delft University of Technology), Juanru Li (Feiyu Tech), Arash Shaghaghi (The University of New South Wales), Nan Sun (The University of New South Wales), Siqi Ma (The University of New South Wales)

Read More

Do We Really Need to Design New Byzantine-robust Aggregation...

Minghong Fang (University of Louisville), Seyedsina Nabavirazavi (Florida International University), Zhuqing Liu (University of North Texas), Wei Sun (Wichita State University), Sundararaja Iyengar (Florida International University), Haibo Yang (Rochester Institute of Technology)

Read More

SHAFT: Secure, Handy, Accurate and Fast Transformer Inference

Andes Y. L. Kei (Chinese University of Hong Kong), Sherman S. M. Chow (Chinese University of Hong Kong)

Read More

TWINFUZZ: Differential Testing of Video Hardware Acceleration Stacks

Matteo Leonelli (CISPA Helmholtz Center for Information Security), Addison Crump (CISPA Helmholtz Center for Information Security), Meng Wang (CISPA Helmholtz Center for Information Security), Florian Bauckholt (CISPA Helmholtz Center for Information Security), Keno Hassler (CISPA Helmholtz Center for Information Security), Ali Abbasi (CISPA Helmholtz Center for Information Security), Thorsten Holz (CISPA Helmholtz Center for Information…

Read More