Announcing AWS Security Reference Architecture Code Examples for Generative AI

Post Syndicated from Ievgeniia Ieromenko original https://aws.amazon.com/blogs/security/announcing-aws-security-reference-architecture-code-examples-for-generative-ai/

Amazon Web Services (AWS) is pleased to announce the release of new Security Reference Architecture (SRA) code examples for securing generative AI workloads. The examples include two comprehensive capabilities focusing on secure model inference and RAG implementations, covering a wide range of security controls and best practices for AWS generative AI services.

These new code examples are available in the AWS SRA Examples Repository and include ready-to-deploy CloudFormation templates for implementing detective security controls such as network segmentation, identity management, encryption, prompt injection detection, and logging and monitoring. The solutions align with the AWS SRA Design Guidance page and demonstrate our commitment to helping customers secure their generative AI implementations.

Customers can get started with these examples by following the implementation instructions for each solution in the AWS SRA Examples Repository Solutions GenAI page. Additional documentation and implementation guidance is available in the AWS SRA Design Guidance Generative AI Architecture Deep Dive.

AWS strives to continuously provide security solutions that help customers meet their security architecture needs. Customers can reach out to the team by submitting an issue in the code repository.

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Ievgeniia Ieromenko

Ievgeniia Ieromenko

Ievgeniia a Security Engineer at AWS, focusing on cloud security architecture and best practices. She is a key contributor to the AWS Security Reference Architecture GitHub repository, helping customers implement secure cloud environments.

Liam Schneider

Liam Schneider

Liam is a Sr. Security Engineer with deep experience in cloud and application security, focused on reducing risk, improving system resilience, and aligning security with business needs. Liam has a strong background in compliance, team leadership, and building secure, scalable solutions across complex environments. He is known for practical, effective approaches to modern security challenges in both enterprise and cloud-first organizations.

Justin Kontny

Justin Kontny

Justin is a Sr. Security Engineer at AWS who combines his passion for software development with expertise in cloud security. He focuses on transforming security from a barrier to a business enabler through innovative AI-driven automation. When not pushing the boundaries of cloud security, Justin enjoys time with his children and being active outdoors.