论文标题

AutoSploit:用于评估安全漏洞可利用性的全自动框架

Autosploit: A Fully Automated Framework for Evaluating the Exploitability of Security Vulnerabilities

论文作者

Moscovich, Noam, Bitton, Ron, Mallah, Yakov, Inokuchi, Masaki, Yagyu, Tomohiko, Kalech, Meir, Elovici, Yuval, Shabtai, Asaf

论文摘要

安全漏洞在系统中的存在并不一定意味着可以利用它。在这项研究中,我们介绍了Autosploit,这是一种评估脆弱性可剥削性的自动框架。给定脆弱的环境和相关的利用,AutoSploit将自动测试环境不同配置的利用,以确定成功利用现有漏洞所必需的特定属性。由于测试所有可能的系统配置是不可行的,因此我们引入了一种有效的测试和搜索方法,浏览环境的所有可能配置。 AutoSploit实施的有效测试过程基于两种算法:广义二进制分割和Barinel,分别用于无噪声和嘈杂的环境。我们实施了提出的框架,并使用实际漏洞对其进行了评估。结果表明,AutoSploit能够自动识别影响无嘈杂和嘈杂环境中利用脆弱性的能力的系统属性。这些重要结果可以用于更准确有效的风险评估。

The existence of a security vulnerability in a system does not necessarily mean that it can be exploited. In this research, we introduce Autosploit -- an automated framework for evaluating the exploitability of vulnerabilities. Given a vulnerable environment and relevant exploits, Autosploit will automatically test the exploits on different configurations of the environment in order to identify the specific properties necessary for successful exploitation of the existing vulnerabilities. Since testing all possible system configurations is infeasible, we introduce an efficient approach for testing and searching through all possible configurations of the environment. The efficient testing process implemented by Autosploit is based on two algorithms: generalized binary splitting and Barinel, which are used for noiseless and noisy environments respectively. We implemented the proposed framework and evaluated it using real vulnerabilities. The results show that Autosploit is able to automatically identify the system properties that affect the ability to exploit a vulnerability in both noiseless and noisy environments. These important results can be utilized for more accurate and effective risk assessment.

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