Anthropic Says Alibaba Must Be Punished For Largest Claude Cloning Attack

An anonymous reader quotes a report from Ars Technica: Anthropic has accused the Chinese firm Alibaba of launching the largest attack yet attempting to clone Claude, as China races to match the capabilities of Anthropic's leading model following Mythos' release and subsequent restriction from foreign markets. Ars obtained a June 10 letter sent to Senators Tim Scott (R-S.C.) and Elizabeth Warren (D-Mass.) one day ahead of a Senate committee hearing on "AI and the American Dream." In the letter, Anthropic shared "new, confidential evidence of the largest campaign to illicitly extract Claude's capabilities we have ever measured."

The attacks occurred between April 22 and June 5, when "operators afliated with Alibaba and Alibaba Qwen, Alibaba's AI lab" allegedly generated "more than 28.8 million exchanges with Claude through almost 25,000 fraudulent accounts," Anthropic said. Violating Claude's terms of service and access restrictions, this campaign "targeted some of Claude's most valuable capabilities, such as agentic reasoning, software engineering, and long-horizon tasks." According to Anthropic, Alibaba evaded detection by "using obfuscation techniques and proxy networks." As Chinese demand for reliable obfuscation techniques increases, Anthropic warned there's already "a growing circumvention economy" to fuel an ever-expanding web of future distillation attacks. [...]

"Alibaba is governed by an independent board, none of whom has any military affiliation," Alibaba said. "Its products and services are built for retail, logistics, and enterprise information technology -- not weapons, defense, or intelligence." Anthropic appears unconvinced, however, that Alibaba isn't working with the Chinese government. In the letter, Anthropic warned that without stronger interventions, these distillation attacks will "help China reach Mythos Preview-level capabilities sooner."

To keep the US ahead of China, Anthropic recommended that Congress pass legislation with three objectives. First, antitrust laws must be updated to allow AI firms to share information about evolving Chinese tactics to deter more threats. Second, the US needs more export controls on chips to hamstring Chinese access to advanced compute so that they simply can't train on US model outputs. That could make conducting distillation attacks pointless, Anthropic suggested. Finally, Congress should pass laws penalizing Chinese labs' "bad behavior" so that it's "more difficult and costly" to rely on distillation attacks to advance Chinese models. Penalties could include limiting Chinese firms from accessing US models or advanced US chips or from relying on data centers outside of China, Anthropic suggested.

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