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Chinese AI firms are siphoning capabilities from American models, CISA warns

Help Net Securityby Anamarija Pogorelec ()3 min read4 · 1 read
AI summary · glm-5.3-flashSummaries by Vani AI

CISA, NSA and FBI warn Chinese AI firms including DeepSeek and Moonshot AI extracted billions of tokens from US frontier models via distillation campaigns.

A joint CISA, NSA and FBI advisory says China-based firms including DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun and Z.AI have run industrial-scale knowledge distillation campaigns against US frontier models such as Claude, GPT, Gemini and Grok since at least late 2024, likely with Chinese government knowledge. The campaigns used gray-market API proxies called transfer stations, premium account pools and traffic routing to bypass restrictions, evade safeguards and exfiltrate billions of tokens used to train models like DeepSeek R1/V3 and Kimi. The agencies challenge DeepSeek's reported $5.6 million training cost and recommend identity verification, usage monitoring, response variation, differential privacy and indicator sharing as defenses.

Key facts
  • Six Chinese AI firms extracted billions of tokens from US frontier models
  • Transfer stations and account pools obscured origin and bypassed usage limits
  • Z.AI distilled data from GPT-5.5 and Claude Opus 4.8 for chain-of-thought reasoning
  • Detection signs include 24/7 usage and anomalous subscription-to-API ratios
  • Mitigations include differential privacy, response variation and indicator sharing
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From the original article

3 min read at helpnetsecurity.com

China-based AI companies are using large-scale knowledge distillation campaigns to copy capabilities from leading U. S. AI models, according to a joint cybersecurity advisory from the CISA, NSA, and FBI.

Help Net Security

By Anamarija Pogorelec · helpnetsecurity.com

Read the full article at Help Net Security

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.