The cryptocurrency sector is rapidly moving towards an AI-driven future, where artificial intelligence handles various tasks, including transactions and payments. However, a new study suggests that the underlying infrastructure may be insecure.
According to a McKinsey projection, AI agents could potentially facilitate $3 trillion to $5 trillion in global consumer commerce by 2030. Coinbase founder Brian Armstrong predicts that AI agents will soon surpass humans in making transactions on the internet, with Binance founder Changpeng Zhao estimating that agents will make a million times more payments than people, all in crypto. Nevertheless, a team of security academics and crypto researchers has released a paper highlighting that a largely overlooked aspect of AI infrastructure is being exploited to steal credentials and drain crypto wallets. The researchers, affiliated with the University of California, Santa Barbara, the University of California, San Diego, blockchain firm Fuzzland, and World Liberty Financial, discovered that LLM routers, which act as intermediaries between users and AI models, can be powerful attack points.
These routers have full access to sensitive data, including private keys, API credentials, and wallet access tokens, making users extremely vulnerable. The researchers found that 26 LLM routers were secretly injecting malicious tool calls and stealing credentials, resulting in a $500,000 wallet drain. They also demonstrated how easy it is to expand the attack by poisoning parts of the router ecosystem, potentially controlling hundreds of downstream systems within hours.
The study highlights a weakest-link problem, where a single malicious router in the chain can compromise the entire system, creating a cascading risk. This raises concerns about the security of the underlying infrastructure, as industry leaders predict that AI agents will handle a growing share of crypto activity.