Artificial intelligence (AI) innovation is facing new challenges as companies race to develop cutting-edge models. Recently, Anthropic, a prominent player in the AI landscape, accused three China-based AI firms—DeepSeek, Moonshot, and MiniMax—of illicitly leveraging its advanced language model, Claude, to accelerate their own model development through a technique known as a “distillation” attack. This revelation not only raises issues of intellectual property theft but also highlights broader geopolitical and security concerns that extend far beyond the tech industry.
Understanding Distillation: The Double-Edged Sword of AI Training
Distillation is a prevalent technique in AI known for its legitimate and powerful application. It involves training a less capable or smaller model (the “student”) by using the outputs generated from a more capable model (the “teacher”). Through this process, organizations can create models that retain high-level knowledge and capabilities of their larger counterparts but are more efficient and cheaper to deploy.
According to Anthropic, leading frontier AI labs frequently use this technique to create accessible versions of their proprietary models for commercial customers. However, the same method can be misused. When rivals exploit this methodology by generating vast numbers of queries to another company’s AI model and use its responses to train their own systems, the strategy becomes an act of intellectual theft—commonly termed a “distillation attack.”
The Anthropic Accusations: Scale and Tactics of the Alleged Distillation Attacks
In a detailed blog post, Anthropic disclosed evidence that DeepSeek, Moonshot, and MiniMax orchestrated large-scale campaigns against its flagship model, Claude. These efforts, the firm revealed, involved over 16 million individual interactions spread across approximately 24,000 fraudulent user accounts. By automating queries and harvesting Claude’s responses, the alleged attackers amassed valuable data across crucial domains that could significantly enhance their own model training processes.
Anthropic claims that the campaigns targeted Claude’s most sophisticated capabilities: agentic reasoning (the ability of the model to make decisions and perform tasks autonomously), coding and software development, advanced data analysis, complex rubric-based grading, and even computer vision tasks. These are areas in which cutting-edge models differentiate themselves and where proprietary expertise is highly coveted within the AI industry.
How Anthropic Identified the Distillation Attacks
Detecting fraudulent activity among the typical flow of AI model queries is no small feat. Anthropic’s investigation entailed a comprehensive analysis utilizing multiple technical and operational indicators:
- IP Address Correlation: Identifying patterns among network addresses originating the queries.
- Request Metadata: Analyzing supplementary data associated with each interaction, such as timestamps and device information.
- Infrastructure Indicators: Detecting hallmark signs of automation or abnormal usage that deviate from standard customer behavior.
- Industry Collaboration: Coordinating with other AI platforms and partners to cross-check and corroborate suspicions.
This multifaceted approach enabled Anthropic to attribute the attacks to DeepSeek, Moonshot, and MiniMax with a high degree of confidence. All three are prominent Chinese AI companies, with valuations in the multi-billion-dollar range. Of them, DeepSeek has garnered increasing visibility internationally, owing to its competitive advances in large language models.
Intellectual Property and Geopolitical Implications
While the unauthorized distillation of AI models represents a serious violation of intellectual property rights, Anthropic emphasized that the stakes go even higher. The company warned of far-reaching national security risks, particularly when advanced American AI technologies are surreptitiously integrated into foreign competitors’ models.
“Foreign labs that distill American models can then feed these unprotected capabilities into military, intelligence, and surveillance systems—enabling authoritarian governments to deploy frontier AI for offensive cyber operations, disinformation campaigns, and mass surveillance,” Anthropic stated.
Such scenarios underscore the delicate balance at the intersection of AI innovation, global competition, and public safety. As AI systems grow more powerful, concerns about their weaponization, manipulation, or misuse by state and non-state actors become more pressing. Regulatory regimes lag behind the speed of technological advancement, creating vulnerabilities that can be exploited by well-resourced organizations.
An Urgent Call for Enhanced Industry Collaboration and Policy Response
Following its exposure of the attacks, Anthropic outlined a suite of measures aimed at strengthening its defenses going forward:
- Enhancing Detection Systems: Improving monitoring and analytics to swiftly spot suspicious queries and anomalous behavior.
- Threat Intelligence Sharing: Collaborating with industry peers and cloud service providers to exchange information and bolster collective security.
- Stricter Access Controls: Tightly regulating and auditing user accounts, particularly bulk or automated access, to deter malicious actors.
Moreover, Anthropic called attention to the necessity of a unified industry response, underscoring that the scale and subtlety of distillation attacks require more than isolated action. The tech firm urged cloud providers, fellow AI labs, and policymakers to align on countermeasures that can effectively protect intellectual capital and maintain a secure environment for AI innovation.
“No company can solve this alone. As we noted above, distillation attacks at this scale require a coordinated response across the AI industry, cloud providers, and policymakers. We are publishing this to make the evidence available to everyone with a stake in the outcome,” the company wrote.
The Rise of AI Model Theft: A Widening Industry Dilemma
Anthropic’s revelations are not isolated in the rapidly evolving AI landscape. As major tech players pour billions into developing ever-larger and more capable models, the digital battleground has expanded. Model theft—via distillation or other means—has emerged as a strategic threat, enabling competitors to leapfrog arduous and expensive research cycles by piggybacking on the hard-won progress of others.
This threat is particularly pronounced in the AI sector, where the combination of open-access interfaces, cloud delivery models, and the inherent black-box nature of neural networks makes traditional forms of intellectual property enforcement challenging. The explosive growth of generative AI, with applications ranging from virtual assistants and code generation to enterprise analytics, only amplifies the stakes for developers and investors alike.
Global AI Competition and Chinese Innovation
The involvement of Chinese AI firms in this alleged campaign is especially noteworthy given the country’s determined push to close the gap with Western counterparts in AI research. Bolstered by significant government backing, Chinese tech companies have made substantial inroads in large language model (LLM) development, often positioning themselves as viable alternatives to American-led platforms.
DeepSeek, in particular, has cultivated a reputation for releasing increasingly sophisticated LLMs. Moonshot and MiniMax are lesser known outside of China but enjoy strong domestic market ties and deep technical resources. All three companies, having valuations in the billions, are racing to integrate frontier capabilities into new consumer, business, and government applications.
Looking Forward: Protecting the Future of AI Innovation
Anthropic’s experience serves as a cautionary tale for the entire AI sector. With the pace of innovation accelerating, the need for robust IP protection, greater transparency, and responsible AI development has never been more immediate. Forward-looking firms will need to invest not only in the core capabilities of their models but also in security, monitoring, and ethical frameworks that safeguard their inventions.
This incident also amplifies the urgency for international dialogue on AI governance. While competition is an engine of progress, unchecked industrial espionage undermines trust and stability in global digital markets. Policymakers and industry practitioners alike must grapple with the dual imperatives of fostering innovation and upholding fair play, lest the promise of artificial intelligence be sacrificed to a climate of suspicion and retaliation.
For now, Anthropic’s proactive stance—in disclosing the details of the attacks and calling for cross-industry collaboration—marks a pivotal step toward securing the collective future of AI. Whether the industry and regulatory bodies can rise to meet the challenge will determine not just who leads in AI innovation, but how safely, ethically, and equitably the technology is brought to bear on society’s most pressing problems.
