救援:制作正则表达式DoS攻击*

Yuju Shen, Yanyan Jiang, Chang Xu, Ping Yu, Xiaoxing Ma, Jian Lu
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引用次数: 37

摘要

具有现代扩展的正则表达式(regex)是最流行的字符串处理工具之一。然而,设计不良的正则表达式会产生指数级的匹配步骤,并在构思良好的字符串输入下导致正则表达式拒绝服务(ReDoS)攻击。本文提出了一种三阶段灰盒分析技术ReScue,用于自动生成ReDoS字符串以突出给定正则表达式的漏洞。救援系统地播种(通过遗传搜索),孵化(通过另一种遗传搜索),并最终泵送(通过专用的正则表达式算法),以产生具有最大搜索时间的字符串。我们实现了ReScue工具,并根据实际项目中的29,088个实际正则对其进行了评估。评估结果显示,与现有最佳技术相比,ReScue发现的攻击字符串多49%,将ReScue应用于流行的GitHub项目,发现了10个以前未知的ReDoS漏洞。
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ReScue: Crafting Regular Expression DoS Attacks*
Regular expression (regex) with modern extensions is one of the most popular string processing tools. However, poorly-designed regexes can yield exponentially many matching steps, and lead to regex Denial-of-Service (ReDoS) attacks under well-conceived string inputs. This paper presents ReScue, a three-phase gray-box analytical technique, to automatically generate ReDoS strings to highlight vulnerabilities of given regexes. ReScue systematically seeds (by a genetic search), incubates (by another genetic search), and finally pumps (by a regex-dedicated algorithm) for generating strings with maximized search time. We implemenmted the ReScue tool and evaluated it against 29,088 practical regexes in real-world projects. The evaluation results show that ReScue found 49% more attack strings compared with the best existing technique, and applying ReScue to popular GitHub projects discovered ten previously unknown ReDoS vulnerabilities.
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