Research And Implementation Of Firmware Vulnerability Mining Technology Based On Binary Static Instrumentation And Feedback Fuzzing

With the rapid development of Mobile Internet,Internet of Things and 5G,IoT devices are widely used in various fields,and the number of devices is experiencing unprecedented growth.However,due to the processor architecture,traditional and mature security analysis technologies,such as Taint Analysis Technology and Fuzz Technology Base on Feedback cannot be applied to the security analysis of IoT device firmware program,resulting in the low efficiency of security analysis for IoT device.This paper proposes a firmware vulnerability mining technology based on binary static instrumentation and feedback fuzzing to solve the problem of network program security analysis for IoT devices.The work of this paper mainly includes:1)Proposing an intelligent firmware interaction technology based on binary static instrumentation,applying binary static instrumentation technology to the simulation of hardware interaction,so that the target program can run on the x86 computer through QEMU;2)A binary static instrumentation technology based on taint information analysis is proposed.The taint analysis technology is applied to the ARM and MIPS architectures,and the binary static instrumentation technology is used to enable the target program to provide information feedback on related execution paths;3)Research and implement fuzzing testing technology based on model constraints and path feedback,based on the two technologies in 1)and 2)combined with fuzzing testing technology,performs feedback fuzz testing on related programs of IoT devices,so that the fuzzing samples are more concerned with the user-input-data related path rather than full execution path.Hence,improve the efficiency of the fuzzing test.After testing and comparison,compared with the current mainstream network protocol fuzzing tools Peach 3 and boofuzz,the Firmware Vulnerability Mining Technology based on Binary Static Instrumentation and Feedback Fuzzing prototype system iootfuzzer proposed in this paper can achieve a higher coverage and improve the efficiency of fuzzing for IoT devices.