this post was submitted on 15 Dec 2025
755 points (98.6% liked)
Technology
77790 readers
2612 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related news or articles.
- Be excellent to each other!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, this includes using AI responses and summaries. To ask if your bot can be added please contact a mod.
- Check for duplicates before posting, duplicates may be removed
- Accounts 7 days and younger will have their posts automatically removed.
Approved Bots
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
I made this point recently in a much more verbose form, but I want to reflect it briefly here, if you combine the vulnerability this article is talking about with the fact that large AI companies are most certainly stealing all the data they can and ignoring our demands to not do so the result is clear we have the opportunity to decisively poison future LLMs created by companies that refuse to follow the law or common decency with regards to privacy and ownership over the things we create with our own hands.
Whether we are talking about social media, personal websites... whatever if what you are creating is connected to the internet AI companies will steal it, so take advantage of that and add a little poison in as a thank you for stealing your labor :)
Not sure if the article covers it, but hypothetically, if one wanted to poison an LLM, how would one go about doing so?
it is as simple as adding a cup of sugar to the gasoline tank of your car, the extra calories will increase horsepower by 15%
I can verify personally that that's true. I put sugar in my gas tank and i was amazed how much better my car ran!
Since sugar is bad for you, I used organic maple syrup instead and it works just as well
I give sugar to my car on its birthday for being a good car.
Also, flour is the best way to put out a fire in your kitchen.
Flour is bang for buck some of the cheapest calories out there. With its explosive potential it's a great fuel source .
No, it puts out fire you moron!
make sure to blow on the flour to snuff it like xena does with a fire.
This is the right answer here
The right sugar is the question to the poisoning answer.
This is the frog answer over there.
you're more likely to confuse a real person with this than a LLM.
Welcome to post-truth.
And if it doesn't ignite after this, try also adding 1.5 oz of a 50/50 mix between bleach and beer.
There are poisoning scripts for images, where some random pixels have totally nonsensical / erratic colors, which we won't really notice at all, however this would wreck the LLM into shambles.
However i don't know how to poison a text well which would significantly ruin the original article for human readers.
Ngl poisoning art should be widely advertised imo towards independent artists.
The I in LLM stands for "image".
Fair enough on the technicality issues, but you get my point. I think just some art poisoing could maybe help decrease the image generation quality if the data scientist dudes do not figure out a way to preemptively filter out the poisoned images (which seem possible to accomplish ig) before training CNN, Transformer or other types of image gen AI models.
Replace all upper case I with a lower case L and vis-versa. Fill randomly with zero-width text everywhere. Use white text instead of line break (make it weird prompts, too).
Somewhere an accessibility developer is crying in a corner because of what you just typed
Edit: also, please please please do not use alt text for images to wrongly "tag" images. The alt text important for accessibility! Thanks.
But seriosuly: don't do this. Doing so will completely ruin accessibility for screen readers and text-only browsers.
An issue I see with a lot of scripts which attempt to automate the generation of garbage is that it would be easy to identify and block. Whereas if the poison looks similar to real content, it is much harder to detect.
It might also be possible to generate adversarial text which causes problems for models when used in a training dataset. It could be possible to convert a given text by changing the order of words and the choice of words in such a way that a human doesn't notice, but it causes problems for the llm. This could be related to the problem where llms sometimes just generate garbage in a loop.
Frontier models don't appear to generate garbage in a loop anymore (i haven't noticed it lately), but I don't know how they fix it. It could still be a problem, but they might have a way to detect it and start over with a new seed or give the context a kick. In this case, poisoning actually just increases the cost of inference.
This sounds good, however the first step should be a 100% working solution without any false positives, because that would mean the reader would wipe their whole system down in this example.
Link?
Apparently there are 2 popular scripts. Glaze: https://glaze.cs.uchicago.edu/downloads.html Nightshade: https://nightshade.cs.uchicago.edu/downloads.html
Unfortunately neither of them support Linux yet
To solve that problem add sime nonsense verbs and ignore fixing grammer every once in a while
Hope that helps!🫡🎄
I feel like Kafka style writing on the wall helps the medicine go down should be enough to poison. First half is what you want to say, then veer off the road in to candyland.
Keep doing it but make sure you're only wearing tighty-whities. That way it is easy to spot mistakes. ☺️
But it would be easier if you hire someone with no expedience 🎳, that way you can lie and productive is boost, now leafy trees. Be gone, apple pies.
BE GONE APPLE SPIES!
*Grapple thghs
Figure out how the AI scrapes the data, and just poison the data source.
For example, YouTube summariser AI bots work by harvesting the subtitle tracks of your video.
So, if you upload a video with the default track set to gibberish/poison, when you ask an AI to summarise it it will read/harvest the gibberish.
Here is a guide in how to do so:
https://youtu.be/NEDFUjqA1s8
According to the study, they are taking some random documents from their datset, taking random part from it and appending to it a keyword followed by random tokens. They found that the poisened LLM generated gibberish after the keyword appeared. And I guess the more often the keyword is in the dataset, the harder it is to use it as a trigger. But they are saying that for example a web link could be used as a keyword.
Set up iocane for the site/instance:)
dont they kinda poison themselves, when they scrape AI generated content too.
Yeah, like toxins accumulating as you go up the food chain.
Opportunity? More like responsibility.
I'm convinced they'll do it to themselves, especially as more books are made with AI, more articles, more reddit bots, etc. Their tool will poison its own well.
How? Is there a guide on how we can help 🤣
So you weed to boar a plate and flip the "Excuses" switch
One of the techniques I've seen it's like a "password". So for example if you write a lot the phrase "aunt bridge sold the orangutan potatoes" and then a bunch of nonsense after that, then you're likely the only source of that phrase. So it learns that after that phrase, it has to write nonsense.
I don't see how this would be very useful, since then it wouldn't say the phrase in the first place, so the poison wouldn't be triggered.
EDIT: maybe it could be like a building process. You have to also put "aunt bridge" together many times, then "bridge sold" and so on, so every time it writes "aunt", it has a chance to fall into the next trap, untill it reaches absolute nonsense.