Why Policy in Amazon Bedrock AgentCore chose Cedar for securing agentic workflows

This article explains why Amazon Bedrock AgentCore chose Cedar for securing autonomous AI agents through policy-based authorization.

• LLMs are non-deterministic and untrusted; authorization controls must sit outside the agent
• AgentCore Gateway enforces Cedar policies between agents and tools, blocking everything by default
• Cedar is purpose-built for authorization: readable, analyzable, and deterministic
• Neuro-symbolic AI translates natural language policies to Cedar with automated verification
• Cedar Analysis detects logical errors, conflicts, and policy redundancies using mathematical reasoning
• Cedar policies are human-readable and auditable for compliance and security teams
• Deterministic "default deny, forbid wins" semantics ensure predictable authorization decisions
• Tool filtering prevents agents from attempting to invoke denied tools

Cedar enables scalable, mathematically verified policy management for autonomous agents operating in production environments.