MalNet: a binary-centric network-level profiling of IoT malware

MalNet: a binary-centric network-level profiling of IoT malware

연구 분야: Safety

학회: IMC '22: Proceedings of the 22nd ACM Internet Measurement Conference

Where are the IoT C2 servers located? What vulnerabilities does IoT malware try to exploit? What DDoS attacks are launched in practice? In this work, we conduct a large scale study to answer these questions. Specifically, we collect and dynamically analyze 1447 malware binaries on the day that they become publicly known between March 2021 and March 2022 from VirusTotal and MalwareBazaar. By doing this, we are able to observe and profile their behavior at the network level including: (a) C2 communication, (b) proliferation, and (c) issued DDoS attacks. Our comprehensive study provides the following key observations. First, we quantify the elusive behavior of C2 servers: 91% of the time a server does not respond to a second probe four hours after a successful probe. In addition, we find that 15% of the live servers that we find are not known by threat intelligence feeds available on VirusTotal. Second, we find that the IoT malware relies on fairly old vulnerabilities in its proliferation. Our binaries attempt to exploit 12 different vulnerabilities with 9 of them more than 4 years old, while the most recent one was 5 months old. Third, we observe the launch of 42 DDoS attacks that span 8 types of attacks, with two types of attacks targeting gaming servers. The promising results indicate the significant value of using a dynamic analysis approach that includes active measurements and probing towards detecting and containing IoT botnets.