一个引擎来模糊它们:通用语言处理器测试与语义验证

Yongheng Chen, Rui Zhong, Hong Hu, Hangfan Zhang, Yupeng Yang, Dinghao Wu, Wenke Lee
{"title":"一个引擎来模糊它们:通用语言处理器测试与语义验证","authors":"Yongheng Chen, Rui Zhong, Hong Hu, Hangfan Zhang, Yupeng Yang, Dinghao Wu, Wenke Lee","doi":"10.1109/SP40001.2021.00071","DOIUrl":null,"url":null,"abstract":"Language processors, such as compilers and interpreters, are indispensable in building modern software. Errors in language processors can lead to severe consequences, like incorrect functionalities or even malicious attacks. However, it is not trivial to automatically test language processors to find bugs. Existing testing methods (or fuzzers) either fail to generate high-quality (i.e., semantically correct) test cases, or only support limited programming languages.In this paper, we propose POLYGLOT, a generic fuzzing framework that generates high-quality test cases for exploring processors of different programming languages. To achieve the generic applicability, POLYGLOT neutralizes the difference in syntax and semantics of programming languages with a uniform intermediate representation (IR). To improve the language validity, POLYGLOT performs constrained mutation and semantic validation to preserve syntactic correctness and fix semantic errors. We have applied POLYGLOT on 21 popular language processors of 9 programming languages, and identified 173 new bugs, 113 of which are fixed with 18 CVEs assigned. Our experiments show that POLYGLOT can support a wide range of programming languages, and outperforms existing fuzzers with up to 30× improvement in code coverage.","PeriodicalId":6786,"journal":{"name":"2021 IEEE Symposium on Security and Privacy (SP)","volume":"39 1","pages":"642-658"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":"{\"title\":\"One Engine to Fuzz ’em All: Generic Language Processor Testing with Semantic Validation\",\"authors\":\"Yongheng Chen, Rui Zhong, Hong Hu, Hangfan Zhang, Yupeng Yang, Dinghao Wu, Wenke Lee\",\"doi\":\"10.1109/SP40001.2021.00071\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Language processors, such as compilers and interpreters, are indispensable in building modern software. Errors in language processors can lead to severe consequences, like incorrect functionalities or even malicious attacks. However, it is not trivial to automatically test language processors to find bugs. Existing testing methods (or fuzzers) either fail to generate high-quality (i.e., semantically correct) test cases, or only support limited programming languages.In this paper, we propose POLYGLOT, a generic fuzzing framework that generates high-quality test cases for exploring processors of different programming languages. To achieve the generic applicability, POLYGLOT neutralizes the difference in syntax and semantics of programming languages with a uniform intermediate representation (IR). To improve the language validity, POLYGLOT performs constrained mutation and semantic validation to preserve syntactic correctness and fix semantic errors. We have applied POLYGLOT on 21 popular language processors of 9 programming languages, and identified 173 new bugs, 113 of which are fixed with 18 CVEs assigned. Our experiments show that POLYGLOT can support a wide range of programming languages, and outperforms existing fuzzers with up to 30× improvement in code coverage.\",\"PeriodicalId\":6786,\"journal\":{\"name\":\"2021 IEEE Symposium on Security and Privacy (SP)\",\"volume\":\"39 1\",\"pages\":\"642-658\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"31\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Symposium on Security and Privacy (SP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SP40001.2021.00071\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Symposium on Security and Privacy (SP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SP40001.2021.00071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31

摘要

语言处理器,如编译器和解释器,在构建现代软件中是不可或缺的。语言处理器中的错误可能导致严重的后果,比如不正确的功能,甚至是恶意攻击。然而,自动测试语言处理器以发现错误并非易事。现有的测试方法(或fuzzers)要么无法生成高质量的(即,语义正确的)测试用例,要么只支持有限的编程语言。在本文中,我们提出了POLYGLOT,这是一个通用的模糊测试框架,可以为探索不同编程语言的处理器生成高质量的测试用例。为了实现通用的适用性,POLYGLOT通过统一的中间表示(IR)消除了编程语言在语法和语义上的差异。为了提高语言的有效性,POLYGLOT执行了约束突变和语义验证,以保持语法正确性和修复语义错误。我们将POLYGLOT应用于9种编程语言的21种流行语言处理器上,发现了173个新bug,修复了113个bug,分配了18个cve。我们的实验表明,POLYGLOT可以支持广泛的编程语言,并且在代码覆盖率方面比现有的fuzzers提高了30倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
One Engine to Fuzz ’em All: Generic Language Processor Testing with Semantic Validation
Language processors, such as compilers and interpreters, are indispensable in building modern software. Errors in language processors can lead to severe consequences, like incorrect functionalities or even malicious attacks. However, it is not trivial to automatically test language processors to find bugs. Existing testing methods (or fuzzers) either fail to generate high-quality (i.e., semantically correct) test cases, or only support limited programming languages.In this paper, we propose POLYGLOT, a generic fuzzing framework that generates high-quality test cases for exploring processors of different programming languages. To achieve the generic applicability, POLYGLOT neutralizes the difference in syntax and semantics of programming languages with a uniform intermediate representation (IR). To improve the language validity, POLYGLOT performs constrained mutation and semantic validation to preserve syntactic correctness and fix semantic errors. We have applied POLYGLOT on 21 popular language processors of 9 programming languages, and identified 173 new bugs, 113 of which are fixed with 18 CVEs assigned. Our experiments show that POLYGLOT can support a wide range of programming languages, and outperforms existing fuzzers with up to 30× improvement in code coverage.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信