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Analyzing system software components using API model guided symbolic execution

机译:使用API模型进行指导符号执行分析系统软件组件

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Analyzing real-world software is challenging due to complexity of the software frameworks or APIs they depend on. In this paper, we present a tool, PROMPT, that facilitates the analysis of software components using API model guided symbolic execution. PROMPT has a specification component, PROSE, that lets users define an API model, which consists of a set of data constraints and life-cycle rules that define control-flow constraints among sequentially composed API functions. Given a PROSE model and a software component, PROMPT symbolically executes the component while enforcing the specified API model. PROMPT has been implemented on top of the KLEE symbolic execution engine and has been applied to Linux device drivers from the video, sound, and network subsystems and to some vulnerable components of BlueZ, the implementation of the Bluetooth protocol stack for the Linux kernel. PROMPT detected two new and four known memory vulnerabilities in some of the analyzed system software components.
机译:分析现实世界软件由于软件框架或API的复杂性而挑战。在本文中,我们介绍了一种工具,提示,促进了使用API​​模型引导符号执行的软件组件的分析。提示有一个规范组件,ProSe,它允许用户定义API模型,该模型包括一组数据约束和生命周期规则,该数据约束和生命周期规则定义顺序组合的API函数之间的控制流约束。给定散文模型和软件组件,提示象征性地在强制执行指定的API模型时执行组件。提示已在Klee符号执行引擎的顶部实现,已应用于来自视频,声音和网络子系统的Linux设备驱动程序以及蓝Z的一些易受攻击的组件,实现Linux内核的蓝牙协议栈的实现。提示在某些分析的系统软件组件中检测到两个新的和四个已知的内存漏洞。

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