Mahinthan Chandramohan, Yinxing Xue, Zhengzi Xu, Yang Liu, Chia Yuan Cho, Hee Beng Kuan Tan
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引用次数: 161
Abstract
Binary code search has received much attention recently due to its impactful applications, e.g., plagiarism detection, malware detection and software vulnerability auditing. However, developing an effective binary code search tool is challenging due to the gigantic syntax and structural differences in binaries resulted from different compilers, architectures and OSs. In this paper, we propose BINGO — a scalable and robust binary search engine supporting various architectures and OSs. The key contribution is a selective inlining technique to capture the complete function semantics by inlining relevant library and user-defined functions. In addition, architecture and OS neutral function filtering is proposed to dramatically reduce the irrelevant target functions. Besides, we introduce length variant partial traces to model binary functions in a program structure agnostic fashion. The experimental results show that BINGO can find semantic similar functions across architecture and OS boundaries, even with the presence of program structure distortion, in a scalable manner. Using BINGO, we also discovered a zero-day vulnerability in Adobe PDF Reader, a COTS binary.
近年来,二进制代码搜索因其在剽窃检测、恶意软件检测和软件漏洞审计等方面的重要应用而受到广泛关注。然而,开发一个有效的二进制代码搜索工具是具有挑战性的,因为不同的编译器、体系结构和操作系统导致二进制代码的巨大语法和结构差异。在本文中,我们提出了BINGO -一个可扩展和强大的二进制搜索引擎,支持各种架构和操作系统。关键的贡献是一种选择性内联技术,通过内联相关的库和用户定义函数来捕获完整的函数语义。此外,提出了结构和操作系统中立函数滤波,以显著减少不相关的目标函数。此外,我们还引入了长度变化的部分轨迹,以一种与程序结构无关的方式对二元函数进行建模。实验结果表明,即使存在程序结构失真,BINGO也能以可扩展的方式找到跨架构和操作系统边界的语义相似函数。使用BINGO,我们还在Adobe PDF Reader中发现了一个零日漏洞,这是一个COTS二进制文件。