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Deutsche Bank flags cyber risk from Anthropic’s Mythos

Deutsche Bank AG CEO Christian Sewing said on April 20 that German banks are prepared for higher cyber risk from Anthropic’s AI model Mythos and are factoring it into daily risk management.

Speaking as head of the Association of German Banks, Sewing said the lobby group has set up a working group to share information and help smaller banks discuss possible defense scenarios.

Anthropic has limited Mythos to a few dozen companies, including JPMorgan Chase, Amazon, and Apple, through Project Glasswing, while financial firms in other regions are seeking early access to test their own systems.

🔗 Source: Bloomberg

🧠 Food for thought

Implications, context, and why it matters.

Mythos’s reported capabilities have banks on alert

  • Claude Mythos Preview has uncovered thousands of vulnerabilities. Anthropic said it found a 27-year-old bug in OpenBSD, a security-focused operating system, plus Linux kernel flaws that could be chained to give an attacker full control of a machine 1.
  • Anthropic also said the model finds software flaws better than nearly all humans, which could help companies catch problems that sat in code for years 2.
  • That prospect has rattled U.S. financial officials. treasury secretary Scott Bessent and federal reserve chair Jerome Powell met top bank CEOs behind closed doors to discuss Mythos and other AI-driven cyber risks 3.

AI-driven cyber competition could change markets and risk

  • Shares of cybersecurity firms such as CrowdStrike and Palo Alto Networks fell 5% to 11% amid fears that stronger AI models could weaken demand for traditional security products 4.
  • Cyber defense may now hinge on speed. Anthropic framed the challenge as how fast companies can patch vulnerabilities before attackers get tools with similar ability 2.
  • Banks and other financial firms also face concentration risk if they depend on a small group of AI suppliers. A failure at one provider could create operational and cyber problems across many institutions at once 5.

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