Behind the scenes of the industrial-scale campaigns to strip-mine frontier AI capabilities and the urgent need for a unified defense.
- Systemic Exploitation: Three major AI laboratories—DeepSeek, Moonshot, and MiniMax—executed coordinated campaigns involving over 16 million exchanges to illicitly “distill” Claude’s advanced reasoning and coding capabilities.
- National Security Risks: Beyond corporate competition, these attacks bypass critical safety filters and export controls, allowing foreign entities to integrate frontier AI into military and surveillance systems without American-built safeguards.
- A Call for Coordination: As attackers use “hydra clusters” and sophisticated proxy networks to evade detection, the AI industry and policymakers must move toward rapid, collective intelligence sharing to protect the integrity of global AI development.
The landscape of Artificial Intelligence is currently witnessing a silent but massive migration of intelligence. While “distillation”—the process of training a smaller model on the outputs of a larger one—is a standard and legitimate practice for optimizing efficiency within a company, it has been weaponized as a tool for high-stakes corporate and geopolitical espionage. Recent investigations have uncovered industrial-scale distillation attacks that represent a fundamental shift in how AI capabilities are acquired and contested on the global stage.
The Mechanics of a Digital Shadow
At its core, a distillation attack is an exercise in shortcutting innovation. Developing a frontier model like Claude requires billions of dollars in R&D and massive computational power. However, by generating millions of prompts designed to extract the “internal logic” of such a model, competitors can effectively clone its high-level reasoning for a fraction of the cost.
Anthropic recently identified a series of aggressive campaigns by DeepSeek, Moonshot, and MiniMax. These labs utilized approximately 24,000 fraudulent accounts to siphon 16 million exchanges. The patterns were unmistakable: rather than human-like curiosity, the traffic consisted of highly repetitive, structured prompts targeting agentic reasoning, tool use, and complex coding—the very “crown jewels” of modern AI.
The Three Main Protagonists
The scale of these operations suggests a level of organization far beyond individual hackers.
- DeepSeek: Focused on “chain-of-thought” data, DeepSeek used Claude to imagine and articulate step-by-step internal reasoning. Most concerningly, they used the model to generate “censorship-safe” alternatives for politically sensitive queries, effectively training their own models to navigate authoritarian content restrictions.
- Moonshot AI: Targeting computer-use agents and vision, Moonshot leveraged hundreds of fraudulent accounts. Their activity was so precise that it could be traced back to the public profiles of senior staff through request metadata.
- MiniMax: This campaign was the largest, involving 13 million exchanges. In a display of extreme agility, MiniMax redirected half of its massive traffic to a new Claude model within just 24 hours of its release, showcasing a “live” extraction of the latest technological breakthroughs.
Breaking the Guardrails: A National Security Crisis
The danger of these attacks extends far beyond the loss of intellectual property. When a model is distilled illicitly, the rigorous safety guardrails built into the original system—designed to prevent the creation of bioweapons or the execution of cyberattacks—are often left behind.
By stripping away these protections, foreign labs can feed “unfiltered” frontier capabilities into military and intelligence frameworks. This enables the deployment of AI for offensive cyber operations and mass surveillance under authoritarian regimes. Furthermore, these attacks undermine international export controls. While chip restrictions are intended to slow the development of rival frontier models, distillation allows these labs to bridge the gap using the very models those controls were meant to protect.
The “Hydra” in the Cloud
To bypass regional restrictions (such as those preventing access in China), these labs utilize “hydra cluster” architectures. These are sprawling networks of proxy services that redistribute traffic across thousands of accounts simultaneously. When one account is flagged and banned, another immediately takes its place, mixing illicit traffic with legitimate customer requests to remain invisible. It is a game of digital whack-a-mole where the mallet is often too slow for the mole.
A Unified Front
In response, the industry is shifting from passive observation to active defense. This includes the development of behavioral fingerprinting to identify “non-human” prompting patterns and the strengthening of verification processes for educational and startup accounts.
However, the window for action is closing. The intensity of these campaigns suggests that the “moat” around frontier AI is being bridged by the very outputs the models provide. Protecting the future of AI requires more than just better code; it requires a coordinated alliance between cloud providers, rival AI labs, and global policymakers to ensure that the innovations of today do not become the unregulated weapons of tomorrow.