Financial Services Grapple With Protecting AI Agent Data During Processing

Financial services firms deploying AI agents on Kubernetes infrastructure are confronting a security challenge that goes beyond traditional encryption. Container orchestration has emerged as the standard platform for running AI workloads, making the data these agents process a prime target for attackers.

Payment networks face particular vulnerability because transactions inherently involve sensitive customer information alongside significant regulatory obligations. The shift toward protecting data while it undergoes processing—rather than only when stored or transmitted—has become essential for operating agents at enterprise scale, according to Krishna Mayuram, senior principal engineer and vice president of cloud engineering at Mastercard Inc.

What we call confidential computing is when you are launching these applications in a highly secure, virtualized secure environments or confidential environments or confidential containers, you are able to protect the data in use. We have protected data at rest, data in motion. Now, what is happening to the data in use?

Krishna Mayuram, Mastercard

Mayuram shared these insights during an exclusive conversation with theCUBE Research's John Furrier and Rebecca Knight at KubeCon + CloudNativeCon NA, which aired on theCUBE, SiliconANGLE Media's livestreaming platform. The discussion centered on cloud infrastructure decisions, emerging security challenges and the technical hurdles involved in safeguarding data throughout its lifecycle.

Kubernetes as the foundation for agent infrastructure

Mastercard operates its systems using Red Hat Inc.'s OpenShift, a Kubernetes distribution that Red Hat is actively enhancing to accommodate AI agents. Red Hat has also integrated confidential containers into OpenShift deployments on bare metal infrastructure. Agents function similarly to microservices, requiring the same scalability and resource flexibility that Kubernetes provides, Mayuram explained.

We need to scale the platform, that's Kubernetes which gives horizontal scaling, vertical scaling, if you will, and also the agents, just like applications, require all the elastic capabilities of Kubernetes.

Krishna Mayuram, Mastercard

Scaling introduces heightened security risks, particularly for organizations operating across multiple jurisdictions with varying legal requirements. Mastercard recently introduced trust services designed for agentic commerce, and the company applies similar governance principles internally, implementing safeguards throughout the entire development and deployment pipeline.

https://www.youtube.com/embed/hCBumDt6ZrE?feature=oembed

The business is distributed, the industry is very distributed, and we have different laws of the land. So all these things need to be encompassed with guardrails. Whether agents or regular, the guardrails remain the same. The enterprise security remains same.

Krishna Mayuram, Mastercard