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Anthropic Accuses Chinese AI Labs of Distillation Attacks on Claude Models
DeepSeek, Moonshot, and MiniMax Allegedly Extracted 16 million Responses
Indian AI Firms Urged to Strengthen Defences Against Model Theft
By Business Reporter
New Delhi: February 25, 2026:
The global artificial intelligence industry has been rocked by allegations from Anthropic, the U.S.-based developer of the Claude chatbot, that three prominent Chinese AI labs—DeepSeek, Moonshot AI, and MiniMax—conducted large-scale “distillation attacks” to siphon capabilities from its frontier models. According to Anthropic, these labs created nearly 24,000 fraudulent accounts and generated over 16 million interactions with Claude, effectively cloning its intelligence without incurring the massive costs of training a frontier AI system.
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The accusations have sparked intense debate over intellectual property rights, national security, and the ethics of AI development. For India, which is rapidly expanding its AI ecosystem, the case serves as a cautionary tale about the vulnerabilities of advanced models and the urgent need for protective measures.
What Are Distillation Attacks?
Distillation is a legitimate machine learning technique where a smaller model is trained on the outputs of a larger, more powerful model. Companies often use it to create lightweight versions of their own systems.
However, in a distillation attack, competitors exploit this method by systematically querying a frontier model (like Claude) and using its responses to train their own models. This allows them to bypass:
- High compute costs (billions of dollars in GPUs and infrastructure).
- Massive, curated datasets required for frontier training.
- Export controls and licensing restrictions imposed by governments.
Anthropic argues that the Chinese labs engaged in industrial-scale distillation, effectively committing an intellectual property heist.
Legal and Ethical Dimensions
Legal Violations
- Terms of Service Breach: Creating fraudulent accounts and mass-querying Claude violated Anthropic’s contractual terms.
- Export Control Evasion: U.S. export laws restrict access to frontier AI models by certain foreign entities. Distillation attacks circumvent these restrictions.
- Intellectual Property Theft: Using outputs to train rival models without authorization constitutes misappropriation of proprietary technology.
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Ethical Concerns
- Fairness: Frontier labs invest billions in research; siphoning outputs undermines fair competition.
- Trust: Such practices erode trust in international AI collaboration.
- Hypocrisy Debate: Critics, including Elon Musk, argue that Anthropic itself trained on unlicensed internet data, raising questions about moral consistency.
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Implications for India
India’s AI ecosystem is growing rapidly, with startups and government-backed initiatives aiming to build indigenous large language models. The Anthropic case highlights risk Indian firms must address:
- Model Security: Indian companies must protect APIs from mass-querying and fraudulent accounts.
- Legal Safeguards: Stronger intellectual property laws and enforcement mechanisms are needed to deter model theft.
- International Cooperation: India should collaborate with allies to establish norms against distillation attacks.
- National Security: Frontier AI models have strategic importance; unauthorized siphoning could compromise India’s technological sovereignty.
What Indian Companies Should Do
Defensive Measures
- Rate Limiting: Restrict the number of queries per account to prevent industrial-scale siphoning.
- Anomaly Detection: Deploy AI-driven monitoring to flag suspicious query patterns.
- Watermarking Outputs: Embed invisible markers in responses to detect unauthorized training.
- Access Controls: Restrict API access to verified users and regions.
Strategic Measures
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- Legal Frameworks: Push for amendments in India’s IT Act to explicitly cover AI model theft.
- Industry Collaboration: Form alliances among Indian AI firms to share best practices on security.
- Government Support: Seek state-backed infrastructure for secure AI deployment.
- Global Standards: Advocate for international treaties on AI intellectual property protection.
Expert Opinions
Cybersecurity experts warn that distillation attacks represent the next frontier of digital piracy. Unlike traditional hacking, they exploit legitimate interfaces (APIs) in illegitimate ways. Legal scholars argue that international law is lagging technological realities, leaving companies vulnerable.
Indian AI leaders emphasize that while innovation is crucial, protecting proprietary models is equally important. Without safeguards, India risks losing its competitive edge to foreign labs engaging in parasitic practices.
Timeline of Events
- Feb 23, 2026: Anthropic publishes blog accusing Chinese labs of distillation attacks.
- Feb 24–25, 2026: Media reports reveal details of 16 million queries and 24,000 fake accounts.
- Feb 25, 2026: Debate intensifies, with critics accusing Anthropic of hypocrisy.
Conclusion
The Anthropic vs. Chinese AI labs controversy underscores the fragile balance between innovation, competition, and ethics in the AI industry. Distillation attacks, while technically sophisticated, raise serious legal and moral questions. For India, the case is a wake-up call: as the nation builds its AI future, protecting models from theft and misuse must be a top priority.
By combining technical safeguards, legal reforms, and international cooperation, Indian companies can shield themselves from similar onslaughts and ensure that their innovations remain secure in an increasingly competitive global AI landscape.
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