Honeypots have been used for decades to detect, monitor, and understand attempts of unauthorized use of information systems. Previous studies focused on characterizing the spread of malware, e.g., Mirai and other attacks, or proposed stealthy and interactive architectures to impr
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Honeypots have been used for decades to detect, monitor, and understand attempts of unauthorized use of information systems. Previous studies focused on characterizing the spread of malware, e.g., Mirai and other attacks, or proposed stealthy and interactive architectures to improve honeypot efficiency.
In this paper, we present insights and benefits gained from collaborating with an operational honeyfarm, i.e., a set of honeypots distributed around the globe with centralized data collection. We analyze data of about 400 million sessions over a 15-month period, gathered from a globally distributed honeyfarm consisting of 221 honeypots deployed in 55 countries. Our analysis unveils stark differences among the activity seen by the honeypots-some are contacted millions of times while others only observe a few thousand sessions. We also analyze the behavior of scouters and intruders of these honeypots. Again, some honeypots report orders of magnitude more interactions with command execution than others. Still, diversity is needed since even if we focus on the honeypots with the highest visibility, they see only a small fraction of the intrusions, including only 5% of the files. Thus, although around 2% of intrusions are visible by most of the honeypots in our honeyfarm, the rest are only visible to a few. We conclude with a discussion of the findings of work.@en
