Security & Threat Intelligence · 25.07.2026, 15:29 UTC
Secure multi-tenant AI agents with Amazon Bedrock AgentCore resource-based policies
| Schweregrad | info |
|---|---|
| Kategorie | Security & Threat Intelligence |
| Quelle | AWS Security Blog ↗ |
| Veröffentlicht | 25.07.2026 UTC |
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Software as a service (SaaS) providers building AI-powered applications on Amazon Bedrock AgentCore often need to serve multiple tenants with distinct security requirements from a shared infrastructure. Some tenants require cross-account access from their own Amazon Web Services (AWS) accounts, while others mandate that traffic stay within a private virtual private cloud (VPC) for regulatory compliance. Without centralized resource-level control, managing these diverse requirements can be complex. AgentCore supports resource-based policies, giving you centralized, resource-level control over who can access your AgentCore Runtime and AgentCore Runtime endpoint resources and under what conditions. In this post, you walk through a multi-tenant AI customer service platform where two tenants need different levels of access to the same agent. You learn how to use resource-based policies on AgentCore to grant cross-account access for one tenant while restricting another to VPC-only traffic—all while sharing the same underlying AgentCore Runtime and AgentCore Runtime endpoint. The multi-tenant scenario Imagine you’re an SaaS provider who builds and operates an AI-powered customer service platform. You use AgentCore to deploy intelligent agents that handle customer inquiries, answering product questions, processing returns, and escalating complex issues to human agents. You serve multiple enterprise clients (tenants), each with their own AWS account and unique security requirements: Tenant A: Example Corp is a large retailer operating in AWS account 111122223333. …