AI 服务暂时不可用，以下为来源正文，待恢复后补全翻译。
Enterprises are racing to deploy AI agents that pull from databases, document repositories, and SaaS platforms to automate workflows. But a quiet risk lurks beneath the convenience: a compromised agent manipulated via prompt injection could hand over data the requesting user was never authorized to see. We will show you how to close this gap by moving authorization out of the agent’s code and into the AWS infrastructure itself. Bedrock AgentCore End-to-End Security Architecture (Image Source: aws.amazon.com) This architectural shift ensures that even a fully hijacked agent remains cryptographically constrained to the user’s specific permissions. Just as we discussed the catastrophic consequences of unauthorized data manipulation in our recent breakdown of the Critical GitLab GraphQL Flaw, relying on application-level filtering for AI access is a severe structural weakness. Table of Contents Toggle