AWS Security Blog
Category: Generative AI
Designing for the inevitable: System prompt leakage and mitigations in generative AI applications
System prompts form the foundation of generative AI applications. A system prompt is a collection of instructions and operational context provided to a large language model (LLM) that shapes how the model behaves and interacts with users and tools. System prompts often contain proprietary information, including role definitions, behavioral guidelines, tool descriptions and usage instructions, […]
Why Policy in Amazon Bedrock AgentCore chose Cedar for securing agentic workflows
Agents have agency: they adapt and find multiple ways to solve problems. This autonomy creates a fundamental security challenge: the large language model (LLM) at the heart of the agent is non-deterministic, and its decisions can’t be predicted or guaranteed in advance. It can hallucinate harmful actions with complete confidence. It’s vulnerable to prompt injection […]
Introducing the updated AWS User Guide to Governance, Risk, and Compliance for Responsible AI Adoption
The financial services industry (FSI) is using AI to transform how financial institutions serve their customers. AI solutions can help proactively manage portfolios, automatically refinance mortgages when rates decrease, and negotiate insurance premiums for customers. However, this adoption brings new governance, risk, and compliance (GRC) considerations that organizations need to address. To help FSI customers […]
New compliance guide available: ISO/IEC 42001:2023 on AWS
We have released our latest compliance guide, ISO/IEC 42001:2023 on AWS, which provides practical guidance for organizations designing and operating an Artificial Intelligence Management System (AIMS) using AWS services. As organizations deploy AI and generative AI workloads in the cloud, aligning with globally recognized standards such as ISO/IEC 42001:2023 becomes an important step toward strengthening […]
Five ways to use Kiro and Amazon Q to strengthen your security posture
A Monday morning security alert flags unauthorized access attempts, security group misconfigurations, and AWS Identity and Access Management (IAM) policy violations. Your team needs answers fast. Security teams are using Kiro and Amazon Q Developer to handle repetitive tasks—scanning resources, drafting policies, and researching Common Vulnerabilities and Exposures (CVEs)—so engineers can focus on risk decisions […]
Security posture improvement in the AI era
It’s only been a few weeks since Anthropic announced the Claude Mythos Preview model and launched Project Glasswing with AWS and other leading organizations. This has generated a lot of discussion about the future of cybersecurity and what the ever-increasing capabilities of foundation models mean to organizations. As AWS CISO Amy Herzog pointed out in […]
Building AI defenses at scale: Before the threats emerge
At AWS, we’ve spent decades developing processes and tools that enable us to defend millions of customers simultaneously, wherever they operate around the world. AI has been an extremely helpful addition to the automation our security and threat intelligence teams do every day, and we’re still early in this journey. Our AI-powered log analysis system […]
The Agentic AI Security Scoping Matrix: A framework for securing autonomous AI systems
As generative AI became mainstream, Amazon Web Services (AWS) launched the Generative AI Security Scoping Matrix to help organizations understand and address the unique security challenges of foundation model (FM)-based applications. This framework has been adopted not only by AWS customers across the globe, but also widely referenced by organizations such as OWASP, CoSAI, and […]
Securing Amazon Bedrock API keys: Best practices for implementation and management
July 1, 2026: We updated this post to include guidance for using Amazon Bedrock with Mantle endpoints. Recently, AWS released Amazon Bedrock API keys to make calls to the Amazon Bedrock API. In this post, we provide practical security guidance on effectively implementing, monitoring, and managing this new option for accessing Amazon Bedrock to help […]
Protect your generative AI applications against encoding-based attacks with Amazon Bedrock Guardrails
Amazon Bedrock Guardrails provides configurable safeguards to help you safely build generative AI applications at scale. It offers integrated safety and privacy protections that work across multiple foundation models (FMs), including models available in Amazon Bedrock and models hosted outside Amazon Bedrock from other providers. Bedrock Guardrails currently offers six key safeguards to help prevent […]









