Reconstructing program memory state from multi-gigabyte instruction traces to support interactive analysis

B. Cleary, P. Gorman, Eric Verbeek, M. Storey, M. Salois, F. Painchaud
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引用次数: 2

Abstract

Exploitability analysis is the process of attempting to determine if a vulnerability in a program is exploitable. Fuzzing is a popular method of finding such vulnerabilities, in which a program is subjected to millions of generated program inputs until it crashes. Each program crash indicates a potential vulnerability that needs to be prioritized according to its potential for exploitation. The highest priority vulnerabilities need to be investigated by a security analyst by re-executing the program with the input that caused the crash while recording a trace of all executed assembly instructions and then performing analysis on the resulting trace. Recreating the entire memory state of the program at the time of the crash, or at any other point in the trace, is very important for helping the analyst build an understanding of the conditions that led to the crash. Unfortunately, tracing even a small program can create multimillion line trace files from which reconstructing memory state is a computationally intensive process and virtually impossible to do manually. In this paper we present an analysis of the problem of memory state reconstruction from very large execution traces. We report on a novel approach for reconstructing the entire memory state of a program from an execution trace that allows near realtime queries on the state of memory at any point in a program's execution trace. Finally we benchmark our approach showing storage and performance results in line with our theoretical calculations and demonstrate memory state query response times of less than 200ms for trace files up to 60 million lines.
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从多千兆字节的指令轨迹重构程序内存状态,以支持交互式分析
可利用性分析是试图确定程序中的漏洞是否可利用的过程。模糊测试是发现此类漏洞的一种流行方法,在这种方法中,程序受到数百万生成的程序输入的影响,直到它崩溃。每个程序崩溃都表明一个潜在的漏洞,需要根据其被利用的可能性对其进行优先级排序。安全分析人员需要通过重新执行带有导致崩溃的输入的程序来调查优先级最高的漏洞,同时记录所有已执行的汇编指令的跟踪,然后对结果跟踪执行分析。在崩溃时或在跟踪中的任何其他点重新创建程序的整个内存状态,对于帮助分析人员理解导致崩溃的条件非常重要。不幸的是,即使是跟踪一个小程序也可能创建数百万行跟踪文件,从中重建内存状态是一个计算密集型的过程,实际上不可能手动完成。本文分析了从非常大的执行轨迹中重构存储器状态的问题。我们报告了一种从执行跟踪中重建程序的整个内存状态的新方法,该方法允许在程序执行跟踪中的任何点对内存状态进行近乎实时的查询。最后,我们对我们的方法进行了基准测试,显示存储和性能结果与我们的理论计算一致,并演示了对于多达6000万行的跟踪文件,内存状态查询响应时间小于200ms。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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