Tools like ViProxy let users load-balance multiple Claude Code accounts to maximize access to Fable during its limited window. But Theo predicts Anthropic will kill this method in 2–3 weeks by requiring a rolling cryptographic signature in Claude Code's special OAuth endpoint — and Alibaba is to blame for accelerating that.
Where this was said
At 27:40 · chapter starts 24:10
The Alibaba distillation story is a perfect illustration of how frontier model data gets exfiltrated at scale. Theo explains the alleged mechanism: Alibaba — or more likely a third-party broker — set up discounted Claude Code subscriptions targeted at users in regions where Anthropic accounts are hard to obtain, then routed all traffic through a forwarding proxy that captured every input and output. The result was 28.8 million Claude exchanges across 25,000 fraudulent accounts. [1] — Theo "Alibaba: 28.8M exchanges stolen: Alibaba allegedly scraped 28.8 million Claude exchanges via 25,000 fraudulent accounts to use as model tra…" 25:33 Anthropic's response was a geographic detection code block embedded in Claude Code that checked for signals like Shanghai-based logins — flagged publicly by a user as 'hidden spyware,' then acknowledged by Anthropic's Thorik as a March experiment that had already been superseded by better mitigations. Theo connects this directly to the ViProxy proxy tool he and Ben use to balance accounts, predicting it will be killed within 2–3 weeks once Anthropic adds cryptographic session signatures to Claude Code's proprietary OAuth endpoint. Ben notes that the proxy model is only routing to Claude Code — not to other harnesses — but acknowledges the risk is real.
Alibaba allegedly acquired 28.8 million Claude exchanges via 25,000 fraudulent accounts — likely by offering subsidized Claude Code subscriptions that route all traffic through a data-collecting forwarder. It's not necessarily Alibaba doing it directly; third-party brokers may sell the data to them.
Alibaba allegedly scraped 28.8 million Claude exchanges via 25,000 fraudulent accounts to use as model training data.
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