Daehee Jang, Jaemin Kim, Jiho Kim, Woohyeop Im, Minwoo Jeong, Byeongcheol Choi, Chongkyung Kil
{"title":"论模糊专有系统中的覆盖反馈分析","authors":"Daehee Jang, Jaemin Kim, Jiho Kim, Woohyeop Im, Minwoo Jeong, Byeongcheol Choi, Chongkyung Kil","doi":"10.3390/app14135939","DOIUrl":null,"url":null,"abstract":"Coverage feedback is one of the key mechanisms for improving the effectiveness of fuzzers by measuring and comparing the executed code regions while processing input data. In general, such guidance should always improve the performance of fuzzers to better find unexplored code regions. However, proprietary systems with uncommon I/O interfaces (e.g., UAV system, IoT devices, satellite firmware) require extensive engineering/porting efforts to apply coverage feedback support in developing their fuzzing platform. In this paper, we evaluate the detailed efficacy of coverage feedback in fuzzing based on 44 real-world bugs we found using OSS-Fuzz. Our analysis uncovered when and how code coverage information can be helpful, and our experiment demonstrates that although coverage guidance is always helpful to some extent, its effectiveness depends on various external factors. Therefore, such factors should be carefully considered for optimizing the cost and efficiency in designing the fuzzing architecture of proprietary systems.","PeriodicalId":502388,"journal":{"name":"Applied Sciences","volume":"120 8","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the Analysis of Coverage Feedback in a Fuzzing Proprietary System\",\"authors\":\"Daehee Jang, Jaemin Kim, Jiho Kim, Woohyeop Im, Minwoo Jeong, Byeongcheol Choi, Chongkyung Kil\",\"doi\":\"10.3390/app14135939\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Coverage feedback is one of the key mechanisms for improving the effectiveness of fuzzers by measuring and comparing the executed code regions while processing input data. In general, such guidance should always improve the performance of fuzzers to better find unexplored code regions. However, proprietary systems with uncommon I/O interfaces (e.g., UAV system, IoT devices, satellite firmware) require extensive engineering/porting efforts to apply coverage feedback support in developing their fuzzing platform. In this paper, we evaluate the detailed efficacy of coverage feedback in fuzzing based on 44 real-world bugs we found using OSS-Fuzz. Our analysis uncovered when and how code coverage information can be helpful, and our experiment demonstrates that although coverage guidance is always helpful to some extent, its effectiveness depends on various external factors. Therefore, such factors should be carefully considered for optimizing the cost and efficiency in designing the fuzzing architecture of proprietary systems.\",\"PeriodicalId\":502388,\"journal\":{\"name\":\"Applied Sciences\",\"volume\":\"120 8\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/app14135939\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/app14135939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the Analysis of Coverage Feedback in a Fuzzing Proprietary System
Coverage feedback is one of the key mechanisms for improving the effectiveness of fuzzers by measuring and comparing the executed code regions while processing input data. In general, such guidance should always improve the performance of fuzzers to better find unexplored code regions. However, proprietary systems with uncommon I/O interfaces (e.g., UAV system, IoT devices, satellite firmware) require extensive engineering/porting efforts to apply coverage feedback support in developing their fuzzing platform. In this paper, we evaluate the detailed efficacy of coverage feedback in fuzzing based on 44 real-world bugs we found using OSS-Fuzz. Our analysis uncovered when and how code coverage information can be helpful, and our experiment demonstrates that although coverage guidance is always helpful to some extent, its effectiveness depends on various external factors. Therefore, such factors should be carefully considered for optimizing the cost and efficiency in designing the fuzzing architecture of proprietary systems.