OWL: Understanding and Detecting Concurrency Attacks

Abstract

Just like bugs in single-threaded programs can lead to vulnerabilities, bugs in multithreaded programs can also lead to concurrency attacks. We studied 31 real-world concurrency attacks, including privilege escalations, hijacking code executions, and bypassing security checks. We found that compared to concurrency bugs' traditional consequences (e.g., program crashes), concurrency attacks' consequences are often implicit, extremely hard to be observed and diagnosed by program developers. Moreover, in addition to bug-inducing inputs, extra subtle inputs are often needed to trigger the attacks. These subtle features make existing tools ineffective to detect concurrency attacks. To tackle this problem, we present OWL, the first practical tool that models general concurrency attacks' implicit consequences and automatically detects them. We implemented OWL in Linux and successfully detected five new concurrency attacks, including three confirmed and fixed by developers, and two exploited from previously known and well-studied concurrency bugs. OWL has also detected seven known concurrency attacks. Our evaluation shows that OWL eliminates 94.1% of the reports generated by existing concurrency bug detectors as false positive, greatly reducing developers' efforts on diagnosis. All OWL source code, concurrency attack exploit scripts, and results are available on github.com/hku-systems/owl.