暴露易受攻击的路径:用轻量级符号执行增强静态分析

Guangwei Li, Ting Yuan, Jie Lu, Lian Li, Xiaobin Zhang, Xu Song, Kejun Zhang
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引用次数: 0

摘要

静态分析工具虽然在工业中被广泛采用,但存在较高的误报率。本文旨在通过从给定的缺陷报告中自动搜索易受攻击的路径来改进静态分析工具的结果。为了实现这一目标,我们开发了一种将符号执行技术与静态分析相结合的新工具SATRACER。SATRACER选择性地跳过那些可以通过静态分析持续更新的程序部分,从而大大提高了性能。我们已经将SATRACER应用到21个实际应用程序中。评估结果表明,SATRACER可以在10小时内成功消除商业静态分析工具报告的71.4%的假警报,并确认了29个真正的免费后使用错误和895个真正的空指针解引用错误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exposing Vulnerable Paths: Enhance Static Analysis with Lightweight Symbolic Execution
Static analysis tools, although widely adopted in industry, suffer from a high false positive rate. This paper aims to refine the results of static analysis tools, by automatically searching for a vulnerable path from given defect report. To realize this goal, we develop SATRACER, a novel tool which integrates symbolic execution techniques with static analysis. SATRACER selectively skips those program parts which can be consistently updated by static analysis, thus drastically improving performance. We have applied SATRACER to a set of 21 real-world applications. Evaluation results show that SATRACER can successfully remove 71.4% false alarms reported by a commercial static analysis tool in 10 hours, and confirmed 29 real use-after-free bugs and 895 real null-pointer-dereference bugs.
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