TY - GEN
T1 - Exploring the Frontiers of Firmware Fuzzing
T2 - 20th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2024
AU - Hakim, Safayat Bin
AU - Adil, Muhammad
AU - Batalla, Jordi Mongay
AU - Mavromoustakis, Constandinos X.
AU - Song, Houbing Herbert
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The aim of this study is to investigate into μ AFL, a non-intrusive, feedback-driven fuzzing framework, evaluated on Cortex M4 embedded systems and Unix platforms, focusing on the STM32F407VE Cortex M4 microcontroller. By leveraging the SEGGER J-Trace Pro for trace collection, it demonstrates μAFL's utility beyond its traditional scope, showcasing its efficacy in both embedded and general-purpose computing environments. Our analysis, enriched by juxtaposing μAFL's capabilities with traditional AFL, emphasizes the adaptability and effectiveness of fuzzing methodologies in firmware security enhancement. Furthermore, the study provides a deep understanding of fuzzing execution on different hardware, presenting an execution strategy for the STM32F407VE that highlights the framework's potential in identifying vulnerabilities, evidenced by tests on specific firmware programs such as an LED blinking program integrated with semihosting breakpoints and ETM tracing. The use of uninitialized memory sections and strategically placed break-points offers significant insights into the firmware's execution flow. The results of our comparative analysis clearly show that μ AFL excels at uncovering vulnerabilities, reinforcing the need for evolving fuzzing methodologies to build stronger security systems for embedded devices. This contribution underscores the importance of refining fuzzing techniques to meet the intricate security demands of contemporary computing environments.
AB - The aim of this study is to investigate into μ AFL, a non-intrusive, feedback-driven fuzzing framework, evaluated on Cortex M4 embedded systems and Unix platforms, focusing on the STM32F407VE Cortex M4 microcontroller. By leveraging the SEGGER J-Trace Pro for trace collection, it demonstrates μAFL's utility beyond its traditional scope, showcasing its efficacy in both embedded and general-purpose computing environments. Our analysis, enriched by juxtaposing μAFL's capabilities with traditional AFL, emphasizes the adaptability and effectiveness of fuzzing methodologies in firmware security enhancement. Furthermore, the study provides a deep understanding of fuzzing execution on different hardware, presenting an execution strategy for the STM32F407VE that highlights the framework's potential in identifying vulnerabilities, evidenced by tests on specific firmware programs such as an LED blinking program integrated with semihosting breakpoints and ETM tracing. The use of uninitialized memory sections and strategically placed break-points offers significant insights into the firmware's execution flow. The results of our comparative analysis clearly show that μ AFL excels at uncovering vulnerabilities, reinforcing the need for evolving fuzzing methodologies to build stronger security systems for embedded devices. This contribution underscores the importance of refining fuzzing techniques to meet the intricate security demands of contemporary computing environments.
KW - Embedded Trace Macrocell
KW - firmware fuzzing
KW - firmware security
KW - STM32F407VE
KW - μAFL
UR - http://www.scopus.com/inward/record.url?scp=85199995574&partnerID=8YFLogxK
U2 - 10.1109/IWCMC61514.2024.10592348
DO - 10.1109/IWCMC61514.2024.10592348
M3 - Conference contribution
AN - SCOPUS:85199995574
T3 - 20th International Wireless Communications and Mobile Computing Conference, IWCMC 2024
SP - 1141
EP - 1148
BT - 20th International Wireless Communications and Mobile Computing Conference, IWCMC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 May 2024 through 31 May 2024
ER -