A First Look: Using Linux Containers for Deceptive Honeypots

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The ever-increasing sophistication of malware has made malicious binary collection and analysis an absolute necessity for proactive defenses. Meanwhile, malware authors seek to harden their binaries against analysis by incorporating environment detection techniques, in order to identify if the binary is executing within a virtual environment or in the presence of monitoring tools. For security researchers, it is still an open question regarding how to remove the artifacts from virtual machines to effectively build deceptive "honeypots" for malware collection and analysis. In this paper, we explore a completely different and yet promising approach by using Linux containers. Linux containers, in theory, have minimal virtualization artifacts and are easily deployable on low-power devices. Our work performs the first controlled experiments to compare Linux containers with bare metal and 5 major types of virtual machines. We seek to measure the deception capabilities offered by Linux containers to defeat mainstream virtual environment detection techniques. In addition, we empirically explore the potential weaknesses in Linux containers to help defenders to make more informed design decisions.
Security and privacy
Alexander Kedrowitsch, Danfeng (Daphne) Yao, Gang Wang, and Kirk Cameron. 2017. A First Look: Using Linux Containers for Deceptive Honeypots. In Proceedings of the 2017 Workshop on Automated Decision Making for Active Cyber Defense (SafeConfig '17). Association for Computing Machinery, New York, NY, USA, 15–22. https://doi.org/10.1145/3140368.3140371