AVGuardian: Detecting and Mitigating Publish-Subscribe Overprivilege for Autonomous Vehicle Systems

Abstract

Autonomous vehicle (AV) software systems are emerging to enable rapidly developed self-driving functionalities. Since such systems are responsible for safety-critical decisions, it is necessary to secure them in face of cyber attacks. Through an empirical study of representative AV software systems Baidu Apollo and Autoware, we discover a common over privilege problem with the publish-subscribe communication model widely adopted by AV systems: due to the coarse-grained message design for the publish-subscribe communication, some message fields are over-granted with publish/subscribe permissions. To comply with the least-privilege principle and reduce the attack surface resulting from such problem, we argue that the publish/subscribe permissions should be defined and enforced at the granularity of message fields instead of messages. To systematically address such publish-subscribe over-privilege problems, we present AVGuardian, a system that includes (1) a static analysis tool that detects overprivilege instances in AV software and generates the corresponding access control policies at the message field granularity, and (2) a low-overhead, module-transparent, runtime pub-lish/subscribe permission policy enforcement mechanism to perform online policy violation detection and prevention. Using our detection tool, we are able to automatically detect 581 overprivilege instances in total in Baidu Apollo. To demonstrate the severity, we further constructed several concrete exploits that can lead to vehicle collision and identity theft for AV owners, which have been reported to Baidu Apollo and confirmed as valid. For defense, we prototype and evaluate the policy enforcement mechanism, and find that it has very low overhead, does not affect original AV decision logic, and also is resilient to message replay attacks.