Program Verification Enhanced Precise Analysis of Interrupt-Driven Program Vulnerabilities

Xiang Du, Liangze Yin, Haining Feng, Wei Dong
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Abstract

Due to the non-deterministic occurring of interrupt service routines, vulnerabilities of interrupt-driven programs, such as data race and atomicity violation, are usually hard to discover. Static analysis is an effective method for vulnerability analysis of interrupt-driven programs. However, existing techniques usually produce a large number of false alarms, which limits the application of static analysis in practice. To achieve high precision in vulnerability analysis of interrupt-driven programs, this paper proposes a program verification enhanced precise analysis method. For each potential vulnerability detected by static analysis, we propose a vulnerability validation approach which employs program verification to further automatically verify its feasibility. We have implemented a prototype of our method on top of CBMC. Experimental results on both an academic benchmark and 24 real-world programs show that our method can successfully identify true vulnerabilities and achieve a high precise analysis.
程序验证增强了中断驱动程序漏洞的精确分析
由于中断服务程序的不确定性,中断驱动程序的数据竞争、原子性冲突等漏洞往往难以发现。静态分析是中断驱动程序漏洞分析的有效方法。然而,现有的技术往往会产生大量的虚警,这限制了静态分析在实际中的应用。为了实现中断驱动程序漏洞分析的高精度,本文提出了一种程序验证增强的精确分析方法。针对静态分析检测到的每一个潜在漏洞,我们提出了一种漏洞验证方法,利用程序验证进一步自动验证其可行性。我们已经在CBMC之上实现了我们方法的原型。在一个学术基准和24个实际程序上的实验结果表明,我们的方法能够成功地识别出真实的漏洞,并实现了高精度的分析。
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