Looking At Tarpit and LLM Maze Stats

About 4 years ago, I looked into how effective my SSH tarpits were. Since then, I've also deployed an AI crawler tarpit (technically a maze - it generates an endless number of pages) to serve "content" up to crawlers who ignore my "No Entry" signs. I thought that it might be interesting to take a quick look at trends for both, so this post provides high-level analysis of the statistics that my tarpits generate. SSH Tarpit The analysis that I performed in 2022 used a week of data, so to keep things consistent, I'll do the same here. from(bucket: "telegraf/telegraf_low_granularity") |> range(start: 2026-08-01T00:00:00Z, stop: 2026-08-08T00:00:00Z) |> filter(fn: (r) => r._measurement == "ssh_tarpit") |> filter(fn: (r) => r._field == "after_sum") |> filter(fn: (r) => exists r.country) |> group() |> sum() In the last week, my tarpits have burnt 11.6 days of bot time. In 2022, a single week burnt 20.14 days, meaning that 2026 represents a 42.5% reduction in bot time wasted by the tarpit. Is…