Securing AI agents with temporal policies in Amazon Bedrock AgentCore
Amazon Bedrock AgentCore now enforces stateful authorization rules. Your agents can't bypass workflow sequencing or approve their own high-value actions anymore.
Why it matters
Temporal policies address a critical gap in agent security: the ability to enforce authorization rules that depend on session history and action sequence, not just identity. This moves agents from 'can it do X' to 'should it do X right now, given what it already did'—essential for production deployments in finance, healthcare, and regulated workflows.
The key facts
11 to knowTemporal policies evaluate authorization based on agent session history
Use cases: workflow sequencing enforcement, data fabrication prevention, financial exposure caps, human approval gates
Deployed within Amazon Bedrock AgentCore (AWS's agent platform)
Addresses stateful authorization—a production-readiness blocker for autonomous agents
Feature is live; no timeline/beta language in announcement
Amazon Bedrock AgentCore introduces temporal policies for stateful authorization
Supports workflow sequencing enforcement
Prevents data fabrication via session-history rules
Enables financial exposure caps
Requires human approval for high-value actions
Published Aug 2026 (AWS blog—vendor documentation)
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: Temporal policies in Amazon Bedrock AgentCore let you define stateful rules that evaluate authorization based on an agent's session history. Learn how to enforce workflow sequencing, prevent data fabrication, cap financial exposure, and require human approval for high-value actions.