Although the importance of using static analysis to detect taint-style vulnerabilities in Linux-based embedded firmware is widely recognized, existing approaches are plagued by three major limitations. (a) Approaches based on symbolic execution may miss alias information and therefore suffer from a high false-negative rate. (b) Approaches based on VSA (value set analysis) often provide an over-approximate pointer range. As a result, many false positives could be produced. (c) Existing work for detecting taint-style vulnerability does not consider indirect call resolution, whereas indirect calls are frequently used in Internet-facing embedded devices. As a result, many false negatives could be produced. In this work, we propose a precise demand-driven flow-, context- and field-sensitive alias analysis approach. Based on this new approach, we also design a novel indirect call resolution scheme. Combined with sanitization rule checking, our solution discovers taint-style vulnerabilities by static taint analysis. We implemented our idea with a prototype called EmTaint and evaluated it against 35 real-world embedded firmware samples from six popular vendors. EmTaint discovered at least 192 bugs, including 41 n-day bugs and 151 0-day bugs. At least 115 CVE/PSV numbers have been allocated from a subset of the reported vulnerabilities at the time of writing. Compared to state-of-the-art tools such as KARONTE and SaTC, EmTaint found significantly more bugs on the same dataset in less time.
翻译:尽管使用静态分析来发现Linux基于Linux的嵌入式固态软件中的污点性弱点的重要性得到了广泛承认,但现有方法却受到三大限制的困扰。 (a) 以象征性执行为基础的方法可能忽略别名信息,因此也存在高的虚假负面率。 (b) 以VSA(价值组分析)为基础的方法往往提供过近的间接呼叫范围。因此,可以产生许多虚假的正面效果。 (c) 现有的查明污点性弱点的工作并不考虑间接呼叫式解决办法,而间接电话经常用于因特网嵌入装置。因此,可以产生许多虚假的负值。在这项工作中,我们建议采用精确的以需求驱动的流程、上下和外在外的反偏差分析方法。基于这一新方法,我们还设计了一个新的间接呼叫解决方案。 与消化规则检查相结合,我们的解决办法通过静式的污点分析发现了耐性弱点。 我们用一个名为 EmTaint 的原型应用了我们的想法,并根据35个实体嵌入式的硬质样本进行了评估。