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Microsoft is in a pretty good position to do something that can be valuable to certain institutions.

Imaging every pdf file, every image, every office documents, and every video has a hidden record of the associated Microsoft accounts of all computers it has ever passed through. This should sell well, and realistically nobody can stop them. Why haven't Microsoft done this much earlier?


Sure, there are things you could do legally when falsely accused; and there are things authorities and companies should do.

But ultimately, when you are powerless and can't afford to do the fighting: I'm convinced the only way to protect yourself is to be very mindful about your writing style, and to deliberately corrupt the language through objectively wrong "stylistic elements".


Also through LLMs we now have pieces that are strangely-shaped and are 20x larger...

That probably would not be a fun game to play lol


It's not mentioned in the title, but the payload itself comes with a pretty long wall-of-text comments about biological weapon design and nuclear weapon components. An interesting attempt to make LLMs refuse to touch the payload.

Quote:

> The _index.js payload begins with a large JavaScript block comment containing fake system instructions and policy-triggering content. Because it is inside a comment, it does not affect JavaScript execution. The runtime skips it. The eal malware begins after the comment with a try{eval(...)} wrapper around a large character-code array and a ROT-style substitution function.

> This header appears designed for AI-mediated analysis, not for Node, Bun, or Python. It attempts to derail scanners or analyst copilots that feed the beginning of a file to a language model without clearly isolating the content as untrusted data. In weak pipelines, this can cause refusal behavior, prompt confusion, context pollution, or premature classification before the scanner reaches the actual malware.

> This is not a magical bypass against static detection. YARA rules, entropy checks, AST parsing, string extraction, deobfuscation, and behavioral rules still work. But it is a practical anti-analysis trick against naive LLM-first triage systems.

And I tried to get several hosted models to read the `_index.js` part of the payload through OpenRouter. OpenAI and Anthropic models refused to do anything. Kimi K2.6, GLM 5.1, and Minimax M3 didn't complain though.

Edit: fix formatting


Early Kagi adopter here. I'm actually not aware of most of its AI/LLM features, which is part of why I like it. I noticed Kagi translation when the LinkedIn translator became a meme, but I don't really use any of these features.

That's to say, if one day Kagi also forces AI search summary down my throat and hide the search results, I will definitely leave.


Refund and non-existent customer service aside, this actually seems like a viable way to promote/demote/destroy specific 3rd-party tools from Anthropic's side.


ollama is certainly a "useful" tool. I've lost count how many times my non-technical boss (a professor) said "I can run this model in ollama on my notebook, so obviously it's easy to serve and scale."


I still have em-dash pinned at the top of my clipboard manager. Though nowadays I'm training myself to use some more definitely incorrect punctuations ((like this)) in informal scenarios;; hopefully LLMs won't catch up to such strange usage anytime soon.

Broken sentences. Also useful. Like in some literature works.


I love the ridiculously precise point estimate paired with ridiculously wide 95% confidence interval lol


And to think the date mentioned in the story IS in 2026 feels almost surreal...


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