Fine-Grained Security for AI Agents

This article discusses the need for fine-grained security controls when AI agents access data tools, emphasizing that machine-speed analytics requires machine-enforced policy, identity, masking, filtering, and audit controls. It covers why human-speed policy fails for agents, supported by Apache Iceberg, Polaris, and AgentTrust specs. The architecture includes five layers: storage, catalog, execution, semantics, and agent interface. It provides operational checklists for engineers, data owners, and executives, along with metrics and failure modes. The article is a technical guide for security architects and platform teams.