AflIot: Fuzzing on linux-based IoT device with binary-level instrumentation. Issue 122 (November 2022)

• Record Type: Journal Article
• Authors: Du, Xuechao; Chen, Andong; He, Boyuan; Chen, Hao; Zhang, Fan; Chen, Yan
• Is Part Of: Computers & security. Issue 122(2022)
• Publication Date: 2022-11
• Subjects: Greybox fuzzing -- Internet of things -- On-device -- Binary-level -- Daemon analysis; Computer security -- Periodicals; Electronic data processing departments -- Security measures -- Periodicals; 005.805
• DOI: 10.1016/j.cose.2022.102889
• Languages: English
• ISSNs: 0167-4048

Abstract

Abstract: In recent years, coverage-guided greybox fuzzing has demonstrated its efficiency in detecting security vulnerabilities on traditional devices. Instrumentation information plays a significant role in sophisticated greybox fuzzer such as American Fuzzing Lop to directionally improve coverage and distill seeds. While open-source programs leverage wrapped assemblers to glean instrumentation information, closed-source programs can utilize the emulation-based instrumentation for coverage-guided fuzzing. The pervasiveness of the closed source puts a strong demand for emulation instrumentation. However, the required access to peripherals brings great difficulty in fuzzing on the emulator, especially for those various IoT devices. This paper presents Afl Iot, the first generic on-device fuzzing framework for Linux-based IoT binary programs. By leveraging offset-free binary-level instrumentation, binary programs can avoid unnecessarily rewriting, inherit compatibility of peripherals, and be executed directly on IoT devices by Afl Iot . We evaluate Afl Iot on multiple benchmarks with real-world IoT programs. Afl Iot identified 437 unique crashes in 13 binary programs, including 95 newly confirmed unique crashes. Those crashes demonstrate that Afl Iot is efficient and effective in detecting potential software bugs in binary programs on Linux-based IoT devices.