eval()是邪恶的:JavaScript在PDF恶意软件的研究

A. Lemay, Sylvain P. Leblanc
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引用次数: 3

摘要

近年来,客户端攻击变得非常流行。因此,第三方客户端软件,如Adobe的Acrobat Reader,仍然是一个流行的感染媒介。为了支持他们的恶意活动,PDF恶意软件作者经常转向JavaScript。由于这种恶意意图,来自恶意PDF的JavaScript与来自非恶意PDF的JavaScript明显不同。本文详细分析了两种来源的JavaScript内容:恶意和非恶意的PDF文件,这些文件来自VirusTotal Intelligence上的多个提取,以便概述两种类型的JavaScript在关键字分布上的显著差异。分析表明,恶意软件作者使用的混淆技术和漏洞触发代码的生成创建了工件,例如在正常文件中无法观察到的很少使用的函数的存在。此外,来自恶意PDF文件的JavaScript缺少与常见PDF自动化任务相关的关键字,例如从web获取新内容、与文档交互或与用户交互。这为从以前的研究中检测PDF文件中的恶意JavaScript的推断提供了经验确认,并为基于关键字分布的分类器的创建提供了见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Is eval () Evil : A study of JavaScript in PDF malware
Client-side attacks have become very popular in recent years. Consequently, third party client software, such as Adobe’s Acrobat Reader, remains a popular vector for infections. In order to support their malicious activities, PDF malware authors often turn to JavaScript. Because of this malicious intent, JavaScript from malicious PDF is markedly different than JavaScript from non-malicious PDF. This paper presents a detailed analysis of the content of JavaScript from two sources: malicious and non-malicious PDF files gathered from multiple extractions on VirusTotal Intelligence, in order to provide an overview of the significant differences in the distribution of keywords between the two types of JavaScript. The analysis shows that the obfuscation techniques and the generation of exploit triggering code used by malware authors create artefacts, such as the presence of seldom used functions that are not observable in normal files. Additionally, JavaScript from malicious PDF files lack the keywords associated with common PDF automation tasks such as getting new content from the web, interacting with the document or interacting with the user. This provides empirical confirmation of extrapolations into the detection of malicious JavaScript in PDF files from previous research and provides insight for the creation of a classifier based on keyword distributions.
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