基于VSkLCG的固件跨平台漏洞搜索方法

Mushuai Han, Dongdong Zhao, Hong Lin, D. Zhou, Jianwen Xiang, Zhongjin Liu, Yanzhen Xing
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引用次数: 1

摘要

固件中的漏洞将使系统处于危险之中。由于代码重用,相同的漏洞可能出现在不同的平台上。因此,跨平台搜索漏洞具有重要意义。由于固件源代码难以获取,因此需要在二进制级别搜索漏洞。然而,之前的方法主要是在同一平台上工作,不能直接扩展到跨平台的情况。在本文中,我们提出了一种多级搜索固件跨平台漏洞的方法。给定一个脆弱的函数在一个平台,我们的目标是发现其同源漏洞在另一个平台。为了保证效率,我们识别了一组鲁棒的数字特征,并使用k-最近邻(kNN)算法来获取可能的脆弱函数。为了提高准确率,我们采用基于函数局部调用图和函数之间调用频率的二部匹配算法来计算函数之间的距离。我们已经实现了我们的方法的原型,称为VSkLCG,它支持三个平台(ARM, MIPS, x86)。实验结果表明,该方法可以在保持效率的前提下,以较高的精度搜索固件中的某些漏洞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VSkLCG A Method for Cross-Platform Vulnerability Search in Firmware
Vulnerabilities in firmware will make a system at risk. Because of code reuse, the same vulnerability may occur on different platforms. Therefore, searching vulnerabilities across different platforms is of great significance. Due to the difficulty in obtaining the source code of firmware, there is a need to search vulnerabilities at the binary level. However, the prior methods mainly work at the same platform, which can't be directly extended to the case of cross-platform. In this paper, we propose a multistage method to search cross-platform vulnerabilities in firmware. Given a vulnerable function in a platform, our objective is to find its homologous vulnerability in another platform. To ensure the efficiency, we identify a set of robust numeric features and use the k-Nearest Neighbors (kNN) algorithm to obtain possible vulnerable functions. To improve the accuracy, we adopt the bipartite matching algorithm to calculate the distance between functions based on the local call graphs (LCGs) of functions and the call frequency between functions. We have implemented a prototype of our approach, called VSkLCG, which supports three platforms (ARM, MIPS, x86). The experimental results show that our method can search some vulnerabilities in firmware with a high accuracy while maintaining efficiency.
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