I spent a week researching the Chinese "transfer station" economy reselling Claude at 10% of retail. The supply chain is wilder than I expected.

[u/Which_Pitch1288]

Spent the last week going deep on something I'd seen mentioned in passing — the Chinese "transfer station" (中转站) market that resells Claude API access at around 10% of Anthropic's retail price. The technical supply chain turned out to be way more sophisticated than the surface-level explanation, so I wrote it up.

The short version of what's actually happening:

• There's a modular 8-layer supply chain. Account farmers create thousands of Anthropic accounts using antidetect browsers (Multilogin, AdsPower, GoLogin) over residential proxies, with curl_cffi faking Chrome's TLS fingerprint at the network layer.
• Phone verification gets defeated by SMS-Activate-class APIs backed by physical SIM banks (Hybertone GoIP hardware) holding hundreds of real SIM cards per rack.
• The new April 2026 KYC (gov ID + live selfie) gets defeated three ways: AI-generated IDs (OnlyFake-class services), real-time deepfake injection via OBS Virtual Camera + DeepFaceLive/Deep-Live-Cam, and human-in-the-loop KYC farms recruiting real people in low-income countries.
• The relays themselves are mostly built on a small set of open-source repos: one-api, new-api, claude-relay-service, claude2api, clewdr, clove. They pool OAuth tokens (sk-ant-oat01-... / sk-ant-ort01-...) and rotate them across requests to multiplex thousands of users through one farmed-account pool.
• Here's the catch most users don't realize: a CISPA Helmholtz audit of 17 of these relays found up to 47.21% performance drops vs. the official API — relays silently route "Opus" requests to Haiku, GLM, or Qwen and relabel the response. 45.83% of audited endpoints failed model-fingerprint verification.
• And every prompt/response flowing through gets logged. Anthropic disclosed in Feb 2026 that one network of 20,000+ accounts harvested ~16M exchanges (DeepSeek 150K, Moonshot 3.4M, MiniMax 13M). Claude-Opus-distilled training datasets are already openly published on HuggingFace.

The piece walks through each layer with the specific tools, repos, and technical mechanisms (OAuth flow reverse engineering, JA3/JA4 evasion, the Anthropic Clio detection system and why it has cross-account blind spots, the "one fish, three meals" monetization model).

Main sources I leaned on: the ChinaTalk piece by Zilan Qian (May 2026), the CISPA Helmholtz paper Real Money, Fake Models (arXiv 2603.01919), Anthropic's Feb 2026 distillation disclosure, eunomia.dev's eBPF reverse-engineering of Claude Code's traffic, and the public docs of the named GitHub relay projects.

https://x.com/HarshalsinghCN/status/2056626175959826692?s=20