this post was submitted on 25 May 2025
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I came across Nepenthes today in the comments under a post about AI mazes. It has an option to purposefully generate not just an endless pit of links and pages, but also to deterministically generate random, human-like text for those pages to poison the LLM scrapers as they sink into the tarpit.

After reading that, I thought, could you do something similar to poison image scrapers too?

Like if you have an art hosting site, as long as you can get an AI to fall into the tarpit, you could replace all the art it thinks should be there with distorted images from a dataset.

Or just send it to a kind of “parallel” version of the site that replaces (or heavily distorts) all the images but leaves the text descriptions and tags the same.

I realize there’s probably some sort of filter for any automated image scraper that attempts to sort out low quality images, but if one used similar images to the expected content, that might be enough to get through the filter.

I guess if someone really wanted to poison a model, generating AI replacement images would probably be the most effective way to speed up model decay, but that has much higher energy and processing power overhead.

Anyway, I’m definitely not skilled/knowledgeable enough to make this a thing myself even just as an experiment. But I thought you all might know if someone’s already done it, or you might find the idea fascinating.

What do you think? Any better ideas / suggestions for poisoning art scraping AI?

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[–] Lumidaub@feddit.org 7 points 5 days ago (3 children)

I'd imagine auto generating images that look meaningful but aren't is a lot more involved than generating text. For images we have Glaze and Nightshade which you can apply to your own pictures to protect (Glaze) and/or poison (Nightshade) them.

[–] hallettj@leminal.space 2 points 4 days ago

The images probably don't have to look meaningful as long as it is difficult to distinguish them from real images using a fast, statistical test. Nepenthes uses Markov chains to generate nonsense text that statistically resembles real content, which is a lot cheaper than LLM generation. Maybe Markov chains would also work to generate images? A chain could generate each pixel by based on the previous pixel, or based on neighbors, or some such thing.

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