this post was submitted on 27 Dec 2024
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Evidence for the DDoS attack that bigtech LLM scrapers actually are.

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[–] [email protected] 20 points 2 weeks ago (2 children)

How feasible is it to configure my server to essentially perform a reverse-slow-lorris attack on these LLM bots?

If they won't play nice, then we need to reflect their behavior back onto themselves.

Or perhaps serve a 404, 304 or some other legitimate-looking static response that minimizes load on my server whilst giving then least amount of data to train on.

[–] [email protected] 19 points 2 weeks ago* (last edited 2 weeks ago) (1 children)

The only simple possibles ways are:

  • robot.txt
  • rate limiting by ip
  • blocking by user agent

From the article, they try to bypass all of them:

They also don't give a single flying fuck about robots.txt ...

If you try to rate-limit them, they'll just switch to other IPs all the time. If you try to block them by User Agent string, they'll just switch to a non-bot UA string (no, really). This is literally a DDoS on the entire internet.

It then become a game of whac a mole with big tech 😓

~~The more infuriating for me is that it's done by the big names, and not some random startup.~~ Edit: Now that I think about it, this doesn't prove it is done by Google or Amazon: it can be someone using random popular user agents

[–] [email protected] 7 points 2 weeks ago

I do believe there's blocklists for their IPs out there, that should mitigate things a little

[–] [email protected] 18 points 2 weeks ago* (last edited 2 weeks ago) (1 children)

A possibility to game this kind of bots is to add a hidden link to a randomly generated page, which contain itself a link to another random page, and so one.: The bots will still consume resources but will be stuck parsing random garbage indefinitely.

~~I know there is a website that is doing that, but I forget his name.~~

Edit: This is not the one I had in mind, but I find https://www.fleiner.com/bots/ describes be a good honeypot.