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Cake day: February 9th, 2026

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  • MalwareTech/Marcus Hutchins has an excellent take on this that he posted for the normies on linkedin

    Posted verbatim below to save you from having to read LinkedIn


    Anthropic really won’t let this botnet thing go. It’s so desperate & ridiculous.

    1. 9B parameter models are so weak that they’re essentially useless. There is no reason at all for anyone or anything to be self-replicating them.

    2. Even if you quantize a 9B parameter model down to the smallest possible size (at which point it becomes less than useless), and you run it on regular RAM instead of VRAM (at which point it also becomes painfully slow) it still requires about 5 GB of RAM, which is way more than most IoT device has.

    3. Mirai is already self-propagating across millions of IoT devices without the help of any AI. It’s simply not needed, and it adds unnecessary complexity.

    4. Many IoT devices are ephemeral and their entire OS is reset on reboot, so any code running on the device is gone after reboot. The AI models would also be competing with malware like Mirai, which propagates exponentially faster, and locks down the devices so other malware can’t get in.

    5. Again, why? What is the purpose of this. Anthropic keeps pushing this ridiculous idea but have yet to establish any reason for why this would actually happen, or who would benefit from it.

    6. Any remotely intelligent threat actor would just use a powerful unquantized models to reverse engineer & find vulnerabilities in obscure devices and write normal (AI-free) self-propagating code. Ironically, they typically do this by stealing Anthropic API keys and using Anthropic’s models, not open-weight ones.

    7. Again, why are we self-propagating open-weight models? There is absolutely no reason to do that. The combined processing power of every IoT device on earth would be less than a moderately sized stolen cloud compute GPU instance.

    8. I’m pretty sure Anthropic keeps pushing these ridiculous narratives in an attempt to paint open models as dangerous, thus making the case for banning them. They have been OBSESSED with GLM lately, likely because it’s eating their overpriced lunch. This research is just so deeply unserious, that it’s impossible to believe it’s being done in good faith.













  • The best (worst) part of all is that Jonny keeps going to meta and being like ā€œhey this is badā€ and theyre like ā€œnah that’s intended behaviourā€

    This morning he confirmed that it’s possible to get unlimited arbitrary and untraceable access to their LLM infra through these containers and that meta said that’s ā€œintended behaviourā€

    From jonny:

    So, summary: There is arbitrary inference that is root accessible, everything runs as root, agents can be spawned, exfil is trivial, and a malicious binary can come onto the user’s system through casual prompting, explicit code-sharing through the yet-to-be-released Spaces feature, walked through by a Workflow-Backed Idea, or inspired by a Generated Idea. The also yet-to-be-activated fleet learning system is a system for sharing Ideas in the background between muse instances. coming into focus?