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Title: Randezvous: Making Randomization Effective on MCUs
Internet-of-Things devices such as autonomous vehicular sensors, medical devices, and industrial cyber-physical systems commonly rely on small, resource-constrained microcontrollers (MCUs). MCU software is typically written in C and is prone to memory safety vulnerabilities that are exploitable by remote attackers to launch code reuse attacks and code/control data leakage attacks. We present Randezvous, a highly performant diversification-based mitigation to such attacks and their brute force variants on ARM MCUs. Atop code/data layout randomization and an efficient execute-only code approach, Randezvous creates decoy pointers to camouflage control data in memory; code pointers in the stack are then protected by a diversified shadow stack, local-to-global variable promotion, and return address nullification. Moreover, Randezvous adds a novel delayed reboot mechanism to slow down persistent attacks and mitigates control data spraying attacks via global guards. We demonstrate Randezvous’s security by statistically modeling leakage-equipped brute force attacks under Randezvous, crafting a proof-of-concept exploit that shows Randezvous’s efficacy, and studying a real-world CVE. Our evaluation of Randezvous shows low overhead on three benchmark suites and two applications.  more » « less
Award ID(s):
1955498 1652280
NSF-PAR ID:
10421589
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Annual Computer Security Applications Conference
Page Range / eLocation ID:
28 to 41
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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