B. Cleary, P. Gorman, Eric Verbeek, M. Storey, M. Salois, F. Painchaud
{"title":"Reconstructing program memory state from multi-gigabyte instruction traces to support interactive analysis","authors":"B. Cleary, P. Gorman, Eric Verbeek, M. Storey, M. Salois, F. Painchaud","doi":"10.1109/WCRE.2013.6671279","DOIUrl":null,"url":null,"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.","PeriodicalId":275092,"journal":{"name":"2013 20th Working Conference on Reverse Engineering (WCRE)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 20th Working Conference on Reverse Engineering (WCRE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCRE.2013.6671279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.