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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Cameron Morris (University of Connecticut), Amir Herzberg (University of Connecticut), Bing Wang (University of Connecticut), Samuel Secondo (University of Connecticut)

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Angelo Ruocco, Chris Porter, Claudio Carvalho, Daniele Buono, Derren Dunn, Hubertus Franke, James Bottomley, Marcio Silva, Mengmei Ye, Niteesh Dubey, Tobin Feldman-Fitzthum (IBM Research)

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Zhibo Jin (The University of Sydney), Jiayu Zhang (Suzhou Yierqi), Zhiyu Zhu, Huaming Chen (The University of Sydney)

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Shaofei Li (Key Laboratory of High-Confidence Software Technologies (MOE), School of Computer Science, Peking University), Feng Dong (Huazhong University of Science and Technology), Xusheng Xiao (Arizona State University), Haoyu Wang (Huazhong University of Science and Technology), Fei Shao (Case Western Reserve University), Jiedong Chen (Sangfor Technologies Inc.), Yao Guo (Key Laboratory of High-Confidence Software Technologies…

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