OVER the past several months, the author has gained practical insight into deploying and operating a honeypot, noting that varying hardware, software, and network design can significantly alter outcomes. The DShield honeypot is described as a sensor that pretends to be a vulnerable internet-facing system, collecting data from scans and attacks to show what threat actors are targeting and how.
The author’s SIEM has gathered 8 million logs from 14,000 unique IP addresses, with the logs mainly recording traffic details such as source IP, port, protocol, and URL, while NetFlow logs add direction, byte counts, and dropped packets; the payloads and exploit headers are not shown. According to ChatGPT, AI proved most valuable as a collaborative aid—helping identify data types, point out dead ends, and suggest validation methods rather than acting as an automated solution.
The piece also notes a curious pattern around a unique User-Agent, “libredtail-http,” appearing first in December 2025 across 34 IP addresses, with bursts on the same days and identical request sizes, suggesting an automated botnet scanning for vulnerable Apache servers, Linux web interfaces, and IoT devices. The author concludes that more logs do not automatically yield clearer answers, and recommends central logging, such as a SIEM, plus teamwork to manage tens of thousands or millions of logs.