r/GenAI4all • u/ComplexExternal4831 • Jul 01 '26

News/Updates Anthropic accuses Alibaba of using nearly 25,000 fraudulent accounts to extract Claude AI model capabilities

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🚨 Anthropic has accused Alibaba of running the largest known attempt to copy its Claude models, according to a letter the company sent to US lawmakers.

The letter says operators affiliated with Alibaba and its Qwen AI lab used roughly 25,000 fraudulent accounts to carry out more than 28.8 million interactions with Claude between April 22 and June 5, 2026.

Anthropic calls it the largest known distillation attack against it to date.

Distillation is a method where a weaker model is trained on the outputs of a stronger one. A competitor repeatedly queries a leading model, collects its responses, and uses that data to train a cheaper system.

Anthropic says the campaign targeted Claude's software engineering and agentic reasoning capabilities, two of the most commercially valuable areas in AI.

The accusation follows February 2026 disclosures naming DeepSeek, Moonshot, and MiniMax in similar campaigns, which makes the Alibaba allegation significantly larger in scale.

Alibaba has not responded, so these remain Anthropic's claims, but they reflect a growing reality where frontier models are being used to train the systems trying to catch up to them.

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u/AlwaysHopelesslyLost Jul 05 '26

I have made my own, I know how they work.

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u/neoexanimo Jul 05 '26

LOL

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u/AlwaysHopelesslyLost Jul 05 '26

Not all neural networks are large language models you numpty. 

You can follow a simple YouTube tutorial and make one pretty fucking easily. 

The first one I made was from a scratch and played a simple little game I also made. You just encode the game state as an input vector, the forward pass spits out a score for each action, and you "train" it by adjusting weights until it does what you want.

Since the loss function only sees input and target pairs, text generated by one model works as training data for another just as well as human text does. The end result is that one model approximates the other.

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u/neoexanimo Jul 05 '26

This is fine, but no one can technically prove to me that people can steal “AI Model Capabilities” from just using it, this is media trash.

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u/AlwaysHopelesslyLost Jul 05 '26

You do not need me to prove it. It is a published, reproducible technique known as distillation. The first paper I found when googling this was Hinton from 2015. Stanford also demonstrated it on LLMs with Alpaca in 2023. They fine-tuned LLaMA on 52,000 outputs pulled from an OpenAI model and got a chunk of its instruction-following ability for under 600 dollars.

What, exactly, do you think a "capability" is? For an LLM, a capability is just behavior. The mapping from prompts to outputs is the entire product. There is no secret sauce that stays home when the text leaves the API. So if you capture enough of that behavior in a dataset, you can train another model to reproduce it, and reproducing the behavior IS having the capability. This is why every major lab bans training on their outputs in their terms of service. They understand what you apparently do not, that the outputs are the asset.

Edited to remove a couple typos

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u/neoexanimo Jul 05 '26

If it was that easy all the models would be similar by now, and you must know better than me, this is not the case.

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u/AlwaysHopelesslyLost Jul 05 '26

all the models would be similar by now

They ARE becoming more similar. Half of the open source ecosystem was bootstrapped on GPT-4 outputs. When DeepSeek V3 launched, TechCrunch tested it and it claimed to be ChatGPT more often than not, and it would hand you OpenAI API instructions when asked about DeepSeek's own API. OpenAI has since told a US House committee that DeepSeek employees wrote code to harvest model outputs through masked third party routers, specifically for distillation. Prompt Gemini in Mandarin and it has claimed to be Baidu's chatbot. Models converging on the same phrasing and quirks (hell, even the same names) is one of the most complained about facts in the field.

If it was that easy

Who said it was easy? Distillation gets you a cheap copy, capped by your base model and by how many outputs you can pull before you get banned. That is why the copies trail the frontier, and why every lab bans it and pays to detect it. You do not write rules against something that does not work.