Elie Bursztein of Google DeepMind on Mythos and the Cybersecurity Wake-Up Call for Financial Services

In the AI: Trust but Verify podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Artificial Intelligence Risk, Inc. aicrisk.com , interviews guests about balancing the risk and reward of Artificial Intelligence for you, your business, and society as a whole. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.In this episode, Alec speaks with Elie Bursztein, researcher at Google DeepMind, about why Anthropic’s upcoming Mythos model has become a major wake-up call for cybersecurity and critical infrastructure. Elie explains that AI-driven vulnerability discovery appears to be materially improving, which means the biggest near-term challenge is not just finding flaws but triaging, patching, and operationalizing defenses quickly enough. He outlines what bank and financial-services leaders should be asking their CTOs and CISOs now, including whether their organizations can absorb a wave of patches, prioritize exploitable vulnerabilities, and stress-test their most important systems. The conversation also explores how AI is reshaping penetration testing, bug bounties, SaaS versus in-house software decisions, and the broader systemic risk posed by shared providers and crypto-related systems. Alec and Elie close on a more optimistic note, discussing how increasingly reliable agents can remove drudge work, improve financial education, and raise the baseline of practical expertise for more people.Summary:Mythos Wake-Up Call: Elie argues that new AI models are meaningfully improving vulnerability discovery and raising the urgency of cyber preparedness.Patching Readiness: Organizations need to test whether they can handle sustained bursts of patches across both vendor software and internal code.Smarter Triage: AI-assisted reproduction and exploit testing can help security teams focus first on the vulnerabilities most likely to cause real harm.Systemic Financial Risk: Banks must map dependencies on core providers, segregate critical systems, and plan for degraded or offline operations.AI’s Practical Upside: More reliable agents can automate repetitive work and help broaden access to useful financial and technical guidance.Referenced in this episode:Companies/Organizations:Google DeepMindAnthropicFirefoxFDICU.S. TreasuryVerapathSWIFTOpenAIGoogleFiservJack HenryCOCCAmadeusCapital OneNiceHashCopyright © 2026 by Artificial Intelligence Risk, Inc.