{"title":"Evolving indigestible codes: Fuzzing interpreters with genetic programming","authors":"Sanjay Rawat, F. Duchene, Roland Groz, J. Richier","doi":"10.1109/CICYBS.2013.6597203","DOIUrl":null,"url":null,"abstract":"Browsers have become an interface to perform a plethora of activities. This situation led to the integration of various software components in browsers, including interpreters for many web-friendly scripting languages e.g. JavaScript. In this article, we propose an application of genetic programming to the area of fuzzing the interpreters by generating codes that may trigger crashes and thereby indicating the presence of some hidden vulnerabilities. Based on our previous work on smart fuzzing with genetic approaches, we present here elements for an extension of the concept to fuzz browser interpreters.","PeriodicalId":178381,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence in Cyber Security (CICS)","volume":"30 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Symposium on Computational Intelligence in Cyber Security (CICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICYBS.2013.6597203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Browsers have become an interface to perform a plethora of activities. This situation led to the integration of various software components in browsers, including interpreters for many web-friendly scripting languages e.g. JavaScript. In this article, we propose an application of genetic programming to the area of fuzzing the interpreters by generating codes that may trigger crashes and thereby indicating the presence of some hidden vulnerabilities. Based on our previous work on smart fuzzing with genetic approaches, we present here elements for an extension of the concept to fuzz browser interpreters.
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