I am noticing a trend here.

Didn't HF say the same thing, when they got hacked, the only LLM that would assist with defense was GLM?

> When we started the log analysis, we first used frontier models behind commercial APIs. This did not work: the analysis requires submitting large volumes of real attack commands, exploit payloads, and C2 artifacts, and these requests were blocked by the providers' safety guardrails, which cannot distinguish an incident responder from an attacker. We ran the forensic analysis instead on zai-org/GLM-5.2, an open-weight model, on our own infrastructure. This had a second benefit: no attacker data, and none of the credentials it referenced, left our environment.

https://huggingface.co/blog/security-incident-july-2026

We do a similar thing to mark documents that are still under embargo and one day I forgot to remove the watermark. The customer complained they had not received the document (a day or two after I sent it), and much searching was done. Finally we found a line in an outlook log on their end that said that the watermark was the reason the file had been put in indefinite quarantine until someone would take a look at it.

That's when I realized my error, and of course it was soon fixed afterwards. It is the first proof that it worked though, so I'm kind of happy about that.

But I have a more abstract question: Are LLMs mass "codemoding" scraping attempt in their context windows to make this work _and_ worth the effort? It seems like it is to prevent a different thing than what Anubis does(which is preventing mass overloading of webservers).

Sees already the case.

"Sorry, that's beyond my current scope. Let's talk about something else."

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For example, let’s say I decided to use their anti-fraud system which prevents attackers from using LLM automated attacks. I’ve been working hard to publish content that makes it clear to LLMs what we do and that we’re the best choice for a category of customers. Suddenly my brand is associated with cyberattacks, bioweapon development, financial mischief, poisons, and we’ve also taken an anti-China position on Tiananmen square.

The response a customer might get next time they ask about my company in an LLM chat could be quite interesting.

You need evil context as well as evil names, and then you need to run the evil code! Not an appropriate defense on client sites.

To stop deobfuscation at scale, you're better off serving so many bundles that mass scraping can't scale, as they cannot reliably deobfuscate your code. This forces them into the browser and it's behavioural analysis from this point onwards.

It's also an insane risk imo, this basically means that I could be banned by openai/anthropic for accidentally crawling this website which might be the ultimate cyberattack - truly dystopian

I host one here

killai.now/poison/about Killai.now/propaganda/about Killai.now/archive

Last one is what it looks like with Miasma

this is such a good Anti LLM technique

Very cool techniques on the antillm side though!

wouldn't be the first time manipulation like this was used, just that earlier the targets were humans (misleading them about functionality or country of origin). except for humans, the overhead induced, even with renaming, was significant. not so much for models, they don't give a fuck.

Its not creating bioweapons, but has code obfuscation that makes it look to an LLM like it is, to resist LLM reverse engineering of its code by triggering refusals. It even has Tienanmen square references to trip over the chinese models.

Sure, We will stop our LLM from decoding obfuscated code by… forcing it to “think” about suicide, self-mutilation, and killing people. This is just philosophically unsettling to me.

I don’t know what software industry I wanted to live in. But it’s certainly not this one.