The secret problem in AI infrastructure: Securing MCP servers and LLM workflows

AI agents are increasingly interacting with real infrastructure through MCP servers, APIs, deployment systems, and cloud services. As organizations adopt AI-native workflows, they face a new challenge: securing the secrets, credentials, and machine identities that power them.

This whitepaper examines how MCP and AI agents are reshaping infrastructure security and outlines practical patterns for managing secrets and reducing risk in AI-native systems.

What you'll learn

• How MCP servers and AI agents change the secrets and identity threat model
• Where secrets leak across AI workflows, from prompts to infrastructure access
• Security best practices for MCP servers, machine identities, and AI-native systems
• How dynamic credentials, scoped access, and runtime secret injection reduce risk

AI agents are accessing your infrastructure. Strong secrets management is the foundation for secure AI adoption.