CoCo: Efficient Browser Extension Vulnerability Detection via Coverage-guided, Concurrent Abstract Interpretation

CoCo: Efficient Browser Extension Vulnerability Detection via Coverage-guided, Concurrent Abstract Interpretation

연구 분야: Strategies

학회: CCS '23: Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security

Extensions complement web browsers with additional functionalities and also bring new vulnerability venues, allowing privilege escalations from adversarial web pages to use extension APIs. Prior works on extension vulnerability detection adopt classic static analysis, which is unable to handle dynamic JavaScript features such as those function calls as part of array lookups. At the same time, prior abstract interpretation focuses on lightweight server-side JavaScript, which often cannot scale to client-side extension code due to object explosions in the abstract domain. In this paper, we design, implement and evaluate a novel, coverage-driven, concurrent abstract interpretation framework, called CoCo, to efficiently detect vulnerabilities in browser extensions. On one hand, CoCo parallelizes abstract interpretation with concurrent taint propagation for each branching statement, message passing and content/background scripts to detect vulnerabilities with improved scalability. On the other hand, CoCo prioritizes analysis that increases code coverage, thus further detecting more vulnerabilities. Our evaluation shows that CoCo detects at least 43 zero-day, exploitable, manually-verified extension vulnerabilities that cannot be detected by state-of-the-art works. We responsibly disclosed all the zero-day vulnerabilities to extension developers.