TY - GEN
T1 - Hiding in the shadows
T2 - 34th Annual Computer Security Applications Conference, ACSAC 2018
AU - Proskurin, Sergej
AU - Lengyel, Tamas
AU - Momeu, Marius
AU - Eckert, Claudia
AU - Zarras, Apostolis
N1 - Publisher Copyright:
© 2018 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2018/12/3
Y1 - 2018/12/3
N2 - ARM has become the leading processor architecture for mobile and IoT devices, while it has recently started claiming a bigger slice of the server market pie as well. As such, it will not be long before malware more regularly target the ARM architecture. Therefore, the stealthy operation of Virtual Machine Introspection (VMI) is an obligation to successfully analyze and proactively mitigate this growing threat. Stealthy VMI has proven itself perfectly suitable for malware analysis on Intel's architecture, yet, it often lacks the foundation required to be equally effective on ARM. In this paper, we closely examine both ARMv7 and ARMv8 architectures to identify shortcomings and develop novel techniques necessary for effective virtualization-based dynamic malware analysis. We implement and open-source a prototype, named altp2m, for the open source Xen Project hypervisor on ARM. Compared to traditional VMI approaches, our solution enables hypervisors to dynamically allocate and switch among multiple guest memory views by utilizing the Second Level Address Translation (SLAT). Further, we implement an alternative single-stepping mechanism and leverage the execute-only capability of the SLAT mechanism on ARMv8 to enable stealthy in-guest instrumentation. To target also ARMv7-based systems, we manipulate the TLB organization through altp2m to coordinate the guest kernel execution flow. To demonstrate the effectiveness of our system, we combine all building blocks of our work to form the foundation for the dynamic malware analysis system DRAKVUF on ARM. Overall, our experiments reveal that our novel dynamic analysis system is stealthy, efficient, and is perfectly suited to assist malware analysts to quickly comprehend the behavior and reduce the mitigation time of malware targeting ARM.
AB - ARM has become the leading processor architecture for mobile and IoT devices, while it has recently started claiming a bigger slice of the server market pie as well. As such, it will not be long before malware more regularly target the ARM architecture. Therefore, the stealthy operation of Virtual Machine Introspection (VMI) is an obligation to successfully analyze and proactively mitigate this growing threat. Stealthy VMI has proven itself perfectly suitable for malware analysis on Intel's architecture, yet, it often lacks the foundation required to be equally effective on ARM. In this paper, we closely examine both ARMv7 and ARMv8 architectures to identify shortcomings and develop novel techniques necessary for effective virtualization-based dynamic malware analysis. We implement and open-source a prototype, named altp2m, for the open source Xen Project hypervisor on ARM. Compared to traditional VMI approaches, our solution enables hypervisors to dynamically allocate and switch among multiple guest memory views by utilizing the Second Level Address Translation (SLAT). Further, we implement an alternative single-stepping mechanism and leverage the execute-only capability of the SLAT mechanism on ARMv8 to enable stealthy in-guest instrumentation. To target also ARMv7-based systems, we manipulate the TLB organization through altp2m to coordinate the guest kernel execution flow. To demonstrate the effectiveness of our system, we combine all building blocks of our work to form the foundation for the dynamic malware analysis system DRAKVUF on ARM. Overall, our experiments reveal that our novel dynamic analysis system is stealthy, efficient, and is perfectly suited to assist malware analysts to quickly comprehend the behavior and reduce the mitigation time of malware targeting ARM.
UR - https://www.scopus.com/pages/publications/85060025199
U2 - 10.1145/3274694.3274698
DO - 10.1145/3274694.3274698
M3 - Conference contribution
AN - SCOPUS:85060025199
T3 - ACM International Conference Proceeding Series
SP - 407
EP - 417
BT - ACM International Conference Proceeding Series
PB - Association for Computing Machinery
Y2 - 3 December 2018 through 7 December 2018
ER -