静态检测恶意javascript PDF文档

P. Laskov, Nedim Srndic
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引用次数: 179

摘要

尽管Adobe的PDF查看器最近进行了安全改进,但其底层代码库仍然容易受到新的攻击。在野外观察到的快速发展的PDF恶意软件的稳定流证实了需要新的保护工具,而不是传统的基于签名的扫描仪。在本文中,我们提出了一种基于提取的JavaScript代码的静态分析来检测含有JavaScript的恶意PDF文档的技术。与以前的工作(主要基于动态分析)相比,我们的方法产生的运行时开销降低了一个数量级,并且不需要特殊的检测。由于它的效率,我们能够在从VirusTotal恶意软件上传门户获得的一个非常大的真实数据集上对它进行评估。该方法已被证明对已知和未知恶意软件都有效,适合大规模批量处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Static detection of malicious JavaScript-bearing PDF documents
Despite the recent security improvements in Adobe's PDF viewer, its underlying code base remains vulnerable to novel exploits. A steady flow of rapidly evolving PDF malware observed in the wild substantiates the need for novel protection instruments beyond the classical signature-based scanners. In this contribution we present a technique for detection of JavaScript-bearing malicious PDF documents based on static analysis of extracted JavaScript code. Compared to previous work, mostly based on dynamic analysis, our method incurs an order of magnitude lower run-time overhead and does not require special instrumentation. Due to its efficiency we were able to evaluate it on an extremely large real-life dataset obtained from the VirusTotal malware upload portal. Our method has proved to be effective against both known and unknown malware and suitable for large-scale batch processing.
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