Jiameng Shi (University of Georgia), Wenqiang Li (Independent Researcher), Wenwen Wang (University of Georgia), Le Guan (University of Georgia)

Although numerous dynamic testing techniques have been developed, they can hardly be directly applied to firmware of deeply embedded (e.g., microcontroller-based) devices due to the tremendously different runtime environment and restricted resources on these devices. This work tackles these challenges by leveraging the unique position of microcontroller devices during firmware development. That is, firmware developers have to rely on a powerful engineering workstation that connects to the target device to program and debug code. Therefore, we develop a decoupled firmware testing framework named IPEA, which shifts the overhead of resource-intensive analysis tasks from the microcontroller to the workstation. Only lightweight “needle probes” are left in the firmware to collect internal execution information without processing it. We also instantiated this framework with a sanitizer based on pointer capability (IPEA-San) and a greybox fuzzer (IPEA-Fuzz). By comparing IPEA-San with a port of AddressSanitizer for microcontrollers, we show that IPEA-San reduces memory overhead by 62.75% in real-world firmware with better detection accuracy. Combining IPEA-Fuzz with IPEA-San, we found 7 zero-day bugs in popular IoT libraries (3) and peripheral driver code (4).

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SENSE: Enhancing Microarchitectural Awareness for TEEs via Subscription-Based Notification

Fan Sang (Georgia Institute of Technology), Jaehyuk Lee (Georgia Institute of Technology), Xiaokuan Zhang (George Mason University), Meng Xu (University of Waterloo), Scott Constable (Intel), Yuan Xiao (Intel), Michael Steiner (Intel), Mona Vij (Intel), Taesoo Kim (Georgia Institute of Technology)

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Scrappy: SeCure Rate Assuring Protocol with PrivacY

Kosei Akama (Keio University), Yoshimichi Nakatsuka (ETH Zurich), Masaaki Sato (Tokai University), Keisuke Uehara (Keio University)

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Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering

Rui Zhu (Indiana University Bloominton), Di Tang (Indiana University Bloomington), Siyuan Tang (Indiana University Bloomington), Zihao Wang (Indiana University Bloomington), Guanhong Tao (Purdue University), Shiqing Ma (University of Massachusetts Amherst), XiaoFeng Wang (Indiana University Bloomington), Haixu Tang (Indiana University, Bloomington)

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