Florian Hofhammer (EPFL), Marcel Busch (EPFL), Qinying Wang (EPFL and Zhejiang University), Manuel Egele (Boston University), Mathias Payer (EPFL)

Dynamic analysis of microcontroller-based embedded firmware remains challenging. The general lack of source code availability for Commercial-off-the-shelf (COTS) firmware prevents powerful source-based instrumentation and prohibits compiling the firmware into an executable directly runnable by an analyst. Analyzing firmware binaries requires either acquisition and configuration of custom hardware, or configuration of extensive software stacks built around emulators. In both cases, dynamic analysis is limited in functionality by complex debugging and instrumentation interfaces and in performance by low execution speeds on Microcontroller Units (MCUs) and Instruction Set Architecture (ISA) translation overheads in emulators.

SURGEON provides a performant, flexible, and accurate rehosting approach for dynamic analysis of embedded firmware. We introduce transplantation to transform binary, embedded firmware into a Linux user space process executing natively on compatible high-performance systems through static binary rewriting. In addition to the achieved performance improvements, SURGEON scales horizontally through process instantiation and provides the flexibility to apply existing dynamic analysis tooling for user space processes without requiring adaptations to firmware-specific use cases. SURGEON’s key use cases include debugging binary firmware with off-the-shelf tooling for user space processes and fuzz testing.

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IRRedicator: Pruning IRR with RPKI-Valid BGP Insights

Minhyeok Kang (Seoul National University), Weitong Li (Virginia Tech), Roland van Rijswijk-Deij (University of Twente), Ted "Taekyoung" Kwon (Seoul National University), Taejoong Chung (Virginia Tech)

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EM Eye: Characterizing Electromagnetic Side-channel Eavesdropping on Embedded Cameras

Yan Long (University of Michigan), Qinhong Jiang (Zhejiang University), Chen Yan (Zhejiang University), Tobias Alam (University of Michigan), Xiaoyu Ji (Zhejiang University), Wenyuan Xu (Zhejiang University), Kevin Fu (Northeastern University)

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Detecting Obfuscated Function Clones in Binaries using Machine Learning

Michael Pucher (University of Vienna), Christian Kudera (SBA Research), Georg Merzdovnik (SBA Research)

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