Mythos, the new AI model from Anthropic that has sparked fear and confusion in traditional tech and finance, is also driving a massive shift in how the crypto industry thinks about security. For years, decentralized finance has focused its defenses on smart contracts. Code is audited, vulnerabilities are cataloged, and many common exploits are well understood. But Mythos, a model designed to identify and chain together weaknesses across systems, is pushing attention beyond code and into the infrastructure that supports it. “The bigger risks sit in infrastructure,” said Paul Vijender, head of security at Gauntlet, a risk management firm. “When I think about AI-driven threats, I’m less concerned about smart contract exploits and more focused on AI-assisted attacks against the human and infrastructure layers.” That includes key management systems, signing services, bridges, oracle networks, and the cryptographic layers that connect them. These components are less visible than smart contracts and are often outside traditional audit scope. In fact, this month, web infrastructure provider Vercel, which many crypto companies use, disclosed a security breach that may have exposed customer API keys, prompting crypto projects to rotate credentials and review their code. Vercel traced the intrusion to a compromised Google Workspace connection via the third-party AI tool Context.ai, which an employee used. Mythos belongs to a new class of AI systems built to simulate adversaries. Instead of scanning for known bugs, it explores how protocols interact, testing how small weaknesses can be combined into real-world exploits. That approach has drawn attention beyond crypto. Banks like JP Morgan are increasingly treating AI-driven cyber risk as systemic and are exploring tools like Mythos for stress testing. Earlier this month, Coinbase and Binance both reportedly approached Anthropic to test Mythos. Early findings from models like Mythos have identified weaknesses in the behind