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OWL: Understanding and Detecting Concurrency Attacks

机译:OWL:了解和检测并发攻击

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摘要

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.
机译:就像单线程程序中的错误可能导致漏洞一样,多线程程序中的错误也可能导致并发攻击。我们研究了31种现实世界中的并发攻击,包括特权升级,劫持代码执行和绕过安全检查。我们发现,与并发错误的传统后果(例如程序崩溃)相比,并发攻击的后果通常是隐性的,程序开发人员很难观察和诊断。此外,除了引发错误的输入外,通常还需要额外的细微输入来触发攻击。这些微妙的功能使现有工具无法有效检测并发攻击。为了解决这个问题,我们介绍了OWL,这是第一个实用的工具,它可以为通用并发攻击的隐式后果建模并自动检测它们。我们在Linux中实现了OWL,并成功检测到五种新的并发攻击,包括三项由开发人员确认和修复的并发攻击,以及两项从先前已知且经过充分研究的并发性漏洞中利用的漏洞。 OWL还检测到七种已知的并发攻击。我们的评估表明,OWL消除了现有并发错误检测器生成的94.1%的报告为误报,从而大大减少了开发人员的诊断工作。所有OWL源代码,并发攻击利用脚本以及结果可在github.com/hku-systems/owl上找到。

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