{"title":"FirmUp","authors":"Yaniv David, Nimrod Partush, Eran Yahav","doi":"10.1145/3296957.3177157","DOIUrl":null,"url":null,"abstract":"We present a static, precise, and scalable technique for finding CVEs (Common Vulnerabilities and Exposures) in stripped firmware images. Our technique is able to efficiently find vulnerabilities in real-world firmware with high accuracy. Given a vulnerable procedure in an executable binary and a firmware image containing multiple stripped binaries, our goal is to detect possible occurrences of the vulnerable procedure in the firmware image. Due to the variety of architectures and unique tool chains used by vendors, as well as the highly customized nature of firmware, identifying procedures in stripped firmware is extremely challenging. Vulnerability detection requires not only pairwise similarity between procedures but also information about the relationships between procedures in the surrounding executable. This observation serves as the foundation for a novel technique that establishes a partial correspondence between procedures in the two binaries. We implemented our technique in a tool called FirmUp and performed an extensive evaluation over 40 million procedures, over 4 different prevalent architectures, crawled from public vendor firmware images. We discovered 373 vulnerabilities affecting publicly available firmware, 147 of them in the latest available firmware version for the device. A thorough comparison of FirmUp to previous methods shows that it accurately and effectively finds vulnerabilities in firmware, while outperforming the detection rate of the state of the art by 45% on average.","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"183 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"FirmUp\",\"authors\":\"Yaniv David, Nimrod Partush, Eran Yahav\",\"doi\":\"10.1145/3296957.3177157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a static, precise, and scalable technique for finding CVEs (Common Vulnerabilities and Exposures) in stripped firmware images. Our technique is able to efficiently find vulnerabilities in real-world firmware with high accuracy. Given a vulnerable procedure in an executable binary and a firmware image containing multiple stripped binaries, our goal is to detect possible occurrences of the vulnerable procedure in the firmware image. Due to the variety of architectures and unique tool chains used by vendors, as well as the highly customized nature of firmware, identifying procedures in stripped firmware is extremely challenging. Vulnerability detection requires not only pairwise similarity between procedures but also information about the relationships between procedures in the surrounding executable. This observation serves as the foundation for a novel technique that establishes a partial correspondence between procedures in the two binaries. We implemented our technique in a tool called FirmUp and performed an extensive evaluation over 40 million procedures, over 4 different prevalent architectures, crawled from public vendor firmware images. We discovered 373 vulnerabilities affecting publicly available firmware, 147 of them in the latest available firmware version for the device. A thorough comparison of FirmUp to previous methods shows that it accurately and effectively finds vulnerabilities in firmware, while outperforming the detection rate of the state of the art by 45% on average.\",\"PeriodicalId\":50923,\"journal\":{\"name\":\"ACM Sigplan Notices\",\"volume\":\"183 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Sigplan Notices\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3296957.3177157\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Sigplan Notices","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3296957.3177157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
We present a static, precise, and scalable technique for finding CVEs (Common Vulnerabilities and Exposures) in stripped firmware images. Our technique is able to efficiently find vulnerabilities in real-world firmware with high accuracy. Given a vulnerable procedure in an executable binary and a firmware image containing multiple stripped binaries, our goal is to detect possible occurrences of the vulnerable procedure in the firmware image. Due to the variety of architectures and unique tool chains used by vendors, as well as the highly customized nature of firmware, identifying procedures in stripped firmware is extremely challenging. Vulnerability detection requires not only pairwise similarity between procedures but also information about the relationships between procedures in the surrounding executable. This observation serves as the foundation for a novel technique that establishes a partial correspondence between procedures in the two binaries. We implemented our technique in a tool called FirmUp and performed an extensive evaluation over 40 million procedures, over 4 different prevalent architectures, crawled from public vendor firmware images. We discovered 373 vulnerabilities affecting publicly available firmware, 147 of them in the latest available firmware version for the device. A thorough comparison of FirmUp to previous methods shows that it accurately and effectively finds vulnerabilities in firmware, while outperforming the detection rate of the state of the art by 45% on average.
期刊介绍:
The ACM Special Interest Group on Programming Languages explores programming language concepts and tools, focusing on design, implementation, practice, and theory. Its members are programming language developers, educators, implementers, researchers, theoreticians, and users. SIGPLAN sponsors several major annual conferences, including the Symposium on Principles of Programming Languages (POPL), the Symposium on Principles and Practice of Parallel Programming (PPoPP), the Conference on Programming Language Design and Implementation (PLDI), the International Conference on Functional Programming (ICFP), the International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA), as well as more than a dozen other events of either smaller size or in-cooperation with other SIGs. The monthly "ACM SIGPLAN Notices" publishes proceedings of selected sponsored events and an annual report on SIGPLAN activities. Members receive discounts on conference registrations and free access to ACM SIGPLAN publications in the ACM Digital Library. SIGPLAN recognizes significant research and service contributions of individuals with a variety of awards, supports current members through the Professional Activities Committee, and encourages future programming language enthusiasts with frequent Programming Languages Mentoring Workshops (PLMW).