AWS Security Blog
The AWS AI Security Framework: Securing AI with the right controls, at the right layers, at the right phases
May 26, 2026: We’ve updated this post to reflect recommended core services. TL;DR for busy executives The AWS AI Security Framework helps security leaders move fast and stay secure with AI. Security compounds from day 1 as workloads evolve from prototype to production to scale. Assess first. Request a no-cost SHIP engagement to baseline your […]
Secure AI agent access patterns to AWS resources using Model Context Protocol
AI agents and coding assistants interact with AWS resources through the Model Context Protocol (MCP). Unlike traditional applications with deterministic code paths, agents reason dynamically, choosing different tools or accessing different data depending on context. You must assume an agent can do anything within its granted entitlements, whether OAuth scopes, API keys, or AWS Identity […]
Understanding IAM for Managed AWS MCP Servers
As AI agents become part of your development workflows on Amazon Web Services (AWS), you want them to work with your existing AWS Identity and Access Management (IAM) permissions, not force you to build a separate permissions model. At the same time, you need the flexibility to apply different governance controls when an AI agent […]
Authorizing access to data with RAG implementations
Organizations are increasingly using large language models (LLMs) to provide new types of customer interactions through generative AI-powered chatbots, virtual assistants, and intelligent search capabilities. To enhance these interactions, organizations are using Retrieval-Augmented Generation (RAG) to incorporate proprietary data, industry-specific knowledge, and internal documentation to provide more accurate, contextual responses. With RAG, LLMs use an […]
Implement effective data authorization mechanisms to secure your data used in generative AI applications – part 2
In part 1 of this blog series, we walked through the risks associated with using sensitive data as part of your generative AI application. This overview provided a baseline of the challenges of using sensitive data with a non-deterministic large language model (LLM) and how to mitigate these challenges with Amazon Bedrock Agents. The next […]
Implement effective data authorization mechanisms to secure your data used in generative AI applications – part 1
April 3, 2025: We’ve updated this post to reflect the new 2025 OWASP top 10 for LLM entries. This is part 1 of a two-part blog series. See part 2. Data security and data authorization, as distinct from user authorization, is a critical component of business workload architectures. Its importance has grown with the evolution […]
Network perimeter security protections for generative AI
Generative AI–based applications have grown in popularity in the last couple of years. Applications built with large language models (LLMs) have the potential to increase the value companies bring to their customers. In this blog post, we dive deep into network perimeter protection for generative AI applications. We’ll walk through the different areas of network […]
A walk through AWS Verified Access policies
AWS Verified Access helps improve your organization’s security posture by using security trust providers to grant access to applications. This service grants access to applications only when the user’s identity and the user’s device meet configured security requirements. In this blog post, we will provide an overview of trust providers and policies, then walk through […]







