Category: Artificial Intelligence

Financial services institutions (FSIs) are increasingly adopting AI technologies to drive innovation and improve customer experiences. However, this adoption brings new governance, risk, and compliance (GRC) considerations that organizations need to address. To help FSI customers navigate these challenges, AWS is excited to announce the launch of the AWS User Guide to Governance, Risk and […]

In part 2 of this series, we showed you how to use Amazon SageMaker Studio notebooks with natural language input to assist with threat hunting. This is done by using SageMaker Studio to automatically generate and run SQL queries on Amazon Athena with Amazon Bedrock and Amazon Security Lake. The Security Lake service team and […]

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 best practices using AWS generative AI services. These new code examples are […]

April 9, 2025: We updated content about Amazon Bedrock Guardrails to cover the recently added condition key bedrock:GuardrailIdentifier. March 27, 2025: Two policies in this post were updated. Generative AI applications often involve a combination of various services and features—such as Amazon Bedrock and large language models (LLMs)—to generate content and to access potentially confidential […]

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 […]

January 23, 2025: We updated this post to clarify the definition of indirect prompt injection and provided a new example of indirect prompt injection. Generative AI applications have become powerful tools for creating human-like content, but they also introduce new security challenges, including prompt injections, excessive agency, and others. See the OWASP Top 10 for […]

To support our customers in securing their generative AI workloads on Amazon Web Services (AWS), we are excited to announce the launch of a new AWS Skill Builder course: Securing Generative AI on AWS. This comprehensive course is designed to help security professionals, architects, and artificial intelligence and machine learning (AI/ML) engineers understand and implement […]

Amazon Macie is a managed service that uses machine learning (ML) and deterministic pattern matching to help discover sensitive data that’s stored in Amazon Simple Storage Service (Amazon S3) buckets. Macie can detect sensitive data in many different formats, including commonly used compression and archive formats. However, Macie doesn’t support the discovery of sensitive data […]

The Australian financial services regulator, the Australian Prudential Regulation Authority (APRA), has provided its most substantial guidance on generative AI to date in Member Therese McCarthy Hockey’s remarks to the AFIA Risk Summit 2024. The guidance gives a green light for banks, insurance companies, and superannuation funds to accelerate their adoption of this transformative technology, […]

English | German | French Around the world, organizations are evaluating and embracing artificial intelligence (AI) and machine learning (ML) to drive innovation and efficiency. From accelerating research and enhancing customer experiences to optimizing business processes, improving patient outcomes, and enriching public services, the transformative potential of AI is being realized across sectors. Although using […]