New developments: just a few hours before I post this comment, The Register posted an article about AI crawler traffic. https://www.theregister.com/2025/08/21/ai_crawler_traffic/

Anubis’ developer was interviewed and they posted the responses on their website: https://xeiaso.net/notes/2025/el-reg-responses/

In particular:

Fastly’s claims that 80% of bot traffic is now AI crawlers

In some cases for open source projects, we’ve seen upwards of 95% of traffic being AI crawlers. For one, deploying Anubis almost instantly caused server load to crater by so much that it made them think they accidentally took their site offline. One of my customers had their power bills drop by a significant fraction after deploying Anubis. It’s nuts.

So, yeah. If we believe Xe, OOP’s article is complete hogwash.

That’s why the developer is working on a better detection mechanism. https://xeiaso.net/blog/2025/avoiding-becoming-peg-dependency/

With how much authority you wrote with before, I thought you’d be able to grasp the concept. I’m sorry I assumed better.

THEN (and this is the part you don’t seem to understand) the client process has to waste time solving the challenge, which is, by the way, orders of magnitudes lighter on the server than serving the actual meaningful content, or cancel the request. If a new request is sent during that time, it will still have to waste time solving the challenge. The scraper will get through eventually, but the challenge delays the response and reduces the load on the server because while the scrapers are busy computing, it doesn’t have to serve meaningful content to them.

It’s not client-side because validation happens on the server side. The content won’t be displayed until and unless the server receives a valid response, and the challenge is formulated in such a way that calculating a valid answer will always take a long time. It can’t be spoofed because the server will know that the answer is bullshit. In my example, the server will know that the prime factors returned by the client are wrong because their product won’t be equal to the original semiprime. Delegating to a sub-process won’t work either, because what’s the parent process supposed to do? Move on to another piece of content that is also protected by Anubis?

The point is to waste the client’s time and thus reduce the number of requests the server has to handle, not to prevent scraping altogether.

That’s the great thing about Anubis: it’s not client-side. Not entirely anyways. Similar to public key encryption schemes, it exploits the computational complexity of certain functions to solve the challenge. It can’t just say “solved, let me through” because the client has to calculate a number, based on the parameters of the challenge, that fits certain mathematical criteria, and then present it to the server. That’s the “proof of work” component.

A challenge could be something like “find the two prime factors of the semiprime 1522605027922533360535618378132637429718068114961380688657908494580122963258952897654000350692006139”. This number is known as RSA-100, it was first factorized in 1991, which took several days of CPU time, but checking the result is trivial since it’s just integer multiplication. A similar semiprime of 260 decimal digits still hasn’t been factorized to this day. You can’t get around mathematics, no matter how advanced your AI model is.

The developer is working on upgrades and better tools. https://xeiaso.net/blog/2025/avoiding-becoming-peg-dependency/

The current version of Anubis was made as a quick “good enough” solution to an emergency. The article is very enthusiastic about explaining why it shouldn’t work, but completely glosses over the fact that it has worked, at least to an extent where deploying it and maybe inconveniencing some users is preferable to having the entire web server choked out by a flood of indiscriminate scraper requests.

The purpose is to reduce the flood to a manageable level, not to block every single scraper request.

You can go with Debian (or Devuan), easily. My home server is running Proxmox on metal (Debian-based itself), virtualized OPNSense, and multiple Debian containers on an i3-4150 and previously 4GB RAM (now mis-matched 10GB).