Detect Me If You... Oh Wait. An Internet-Wide View of Self-Revealing Honeypots
Shun Morishita (Yokohama National University)
Takuya Hoizumi (Yokohama National University)
Wataru Ueno (Yokohama National University)
Rui Tanabe (Yokohama National University)
Carlos Hernandez Ganan (TU Delft - Technology, Policy and Management)
Michel van Eeten (TU Delft - Technology, Policy and Management)
Katsunari Yoshioka (Yokohama National University)
Tsutomu Matsumoto (Yokohama National University)
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Abstract
Open-source honeypots are a vital component in the protection of networks and the observation of trends in the threat landscape. Their open nature also enables adversaries to identify the characteristics of these honeypots in order to detect and avoid them. In this study, we investigate the prevalence of 14 open-source honeypots running more or less default configurations, making them easily detectable by attackers. We deploy 20 simple signatures and test them for false positives against servers for domains in the Alexa top 10,000, official FTP mirrors, mail servers in real operation, and real IoT devices running telnet. We find no matches, suggesting good accuracy. We then measure the Internet-wide prevalence of default open-source honeypots by matching the signatures with Censys scan data and our own scans. We discovered 19,208 honeypots across 637 Autonomous Systems that are trivially easy to identify. Concentrations are found in research networks, but also in enterprise, cloud and hosting networks.
While some of these honeypots probably have no operational relevance, e.g., they are student projects, this explanation does not fit the wider population. One cluster of honeypots was confirmed to belong to a well-known security center and was in use for ongoing attack monitoring. Concentrations in an another cluster appear to be the result of government incentives. We contacted 11 honeypot operators and received response from 4 operators, suggesting the problem of lack of network hygiene. Finally, we find that some honeypots are actively abused by attackers for hosting malicious binaries. We notified the owners of the detected honeypots via their network operators and provided recommendations for customization to avoid simple signature-based detection. We also shared our results with the honeypot developers.