{"title":"Dridex:流量分析和ioc自动生成","authors":"L. Rudman, B. Irwin","doi":"10.1109/ISSA.2016.7802932","DOIUrl":null,"url":null,"abstract":"In this paper we present a framework that generates network Indicators of Compromise (IOC) automatically from a malware sample after dynamic runtime analysis. The framework addresses the limitations of manual Indicator of Compromise generation and utilises sandbox environment to perform the malware analysis in. We focus on the generation of network based IOCs from captured traffic files (PCAPs) generated by the dynamic malware analysis. The Cuckoo Sandbox environment is used for the analysis and the setup is described in detail. Accordingly, we discuss the concept of IOCs and the popular formats used as there is currently no standard. As an example of how the proof-of-concept framework can be used, we chose 100 Dridex malware samples and evaluated the traffic and showed what can be used for the generation of network-based IOCs. Results of our system confirm that we can create IOCs from dynamic malware analysis and avoid the legitimate background traffic originating from the sandbox system. We also briefly discuss the sharing of, and application of the generated IOCs and the number of systems that can be used to share them. Lastly we discuss how they can be useful in combating cyber threats.","PeriodicalId":330340,"journal":{"name":"2016 Information Security for South Africa (ISSA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Dridex: Analysis of the traffic and automatic generation of IOCs\",\"authors\":\"L. Rudman, B. Irwin\",\"doi\":\"10.1109/ISSA.2016.7802932\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present a framework that generates network Indicators of Compromise (IOC) automatically from a malware sample after dynamic runtime analysis. The framework addresses the limitations of manual Indicator of Compromise generation and utilises sandbox environment to perform the malware analysis in. We focus on the generation of network based IOCs from captured traffic files (PCAPs) generated by the dynamic malware analysis. The Cuckoo Sandbox environment is used for the analysis and the setup is described in detail. Accordingly, we discuss the concept of IOCs and the popular formats used as there is currently no standard. As an example of how the proof-of-concept framework can be used, we chose 100 Dridex malware samples and evaluated the traffic and showed what can be used for the generation of network-based IOCs. Results of our system confirm that we can create IOCs from dynamic malware analysis and avoid the legitimate background traffic originating from the sandbox system. We also briefly discuss the sharing of, and application of the generated IOCs and the number of systems that can be used to share them. Lastly we discuss how they can be useful in combating cyber threats.\",\"PeriodicalId\":330340,\"journal\":{\"name\":\"2016 Information Security for South Africa (ISSA)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Information Security for South Africa (ISSA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSA.2016.7802932\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Information Security for South Africa (ISSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSA.2016.7802932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dridex: Analysis of the traffic and automatic generation of IOCs
In this paper we present a framework that generates network Indicators of Compromise (IOC) automatically from a malware sample after dynamic runtime analysis. The framework addresses the limitations of manual Indicator of Compromise generation and utilises sandbox environment to perform the malware analysis in. We focus on the generation of network based IOCs from captured traffic files (PCAPs) generated by the dynamic malware analysis. The Cuckoo Sandbox environment is used for the analysis and the setup is described in detail. Accordingly, we discuss the concept of IOCs and the popular formats used as there is currently no standard. As an example of how the proof-of-concept framework can be used, we chose 100 Dridex malware samples and evaluated the traffic and showed what can be used for the generation of network-based IOCs. Results of our system confirm that we can create IOCs from dynamic malware analysis and avoid the legitimate background traffic originating from the sandbox system. We also briefly discuss the sharing of, and application of the generated IOCs and the number of systems that can be used to share them. Lastly we discuss how they can be useful in combating cyber threats.