Amazon Bedrock's Security Model: What Enterprises Actually Need to Know

One of the most common blockers I hear from enterprise teams evaluating generative AI isn’t about model quality — it’s about trust. Where does our data go? Can AWS see our prompts? Will our inputs be used to train someone else’s model? Can we meet our compliance requirements? These are the right questions to ask, and Amazon Bedrock has spent considerable engineering effort making sure the answers are satisfying.

This post walks through the core pillars of Bedrock’s security model: how inference stays private, what AWS commits to around your data, how to keep traffic off the public internet, what compliance certifications are in place, how IAM gives you fine-grained access control, and how AgentCore’s Cedar policies extend that control to the level of individual agent tool calls.