Read all about the latest AWS security features, compliance updates, and hands-on resources in our new, monthly digest posts. You’ll find expert blog posts, new service capabilities, code samples, and workshops.

This month’s AWS Security Blog posts covered identity and access management, threat intelligence, network security, AI-powered security tooling, and multi-account governance. Read on for guidance on restricting console access to expected networks, securing multi-tenant AI agents, preventing data exfiltration, and managing organization-scale migrations.

Secure multi-tenant AI agents with Amazon Bedrock AgentCore resource-based policies
Authors: Satyen Verma, Satveer Khurpa, Prajit Pabbati, Vijay Kumar Samanthapudi, Zohreh Norouzi | Published: June 2, 2026
Learn to use resource-based policies on Amazon Bedrock AgentCore to grant cross-account access for one tenant while restricting another to VPC-only traffic in a shared multi-tenant AI platform.

Customize federated sign-in with new Amazon Cognito Lambda trigger
Authors: Abrom Douglas | Published: June 4, 2026
Learn to use the new inbound federation AWS Lambda trigger for Amazon Cognito to transform, filter, and enrich user attributes from external identity providers before profile creation in your user pool.

Amazon Cognito unlocks advanced capabilities with next-generation infrastructure
Authors: Howie Li, Georgi Baghdasaryan | Published: June 4, 2026
Amazon Cognito introduced high-throughput performance, customer-managed keys for data encryption at rest, and multi-Region replication for business continuity, built on a new storage infrastructure migrated with zero downtime.

Building secure B2C applications with fine-grained access control using Amazon Cognito and Amazon Verified Permissions
Authors: Sowmya Vemuri | Published: June 5, 2026
Learn to build fine-grained access controls for a Streamlit application using Amazon Cognito for authentication and Amazon Verified Permissions with Cedar policies for authorization.

Restrict AWS Management Console access to expected networks with sign-in resource-based policies and RCPs
Authors: Swara Gandhi, Rishi Tripathy | Published: June 24, 2026
Learn to use sign-in resource-based policies and resource control policies to restrict AWS Management Console sign-in to requests from expected networks, such as corporate VPNs and Amazon VPC endpoints.

Gain visibility into DDoS attacks with flow logs in AWS Shield Advanced
Authors: Ken Kitts | Published: June 4, 2026
Learn to configure AWS Shield Advanced attack flow logs to capture traffic metadata during DDoS events, pinpoint sources, verify mitigations, and feed your existing analysis pipelines.

Threat tactic spotlight: Subdomain takeover
Authors: Matt Gurr, Ariam Michael, Geoff Sweet, Luis Pastor | Published: June 16, 2026
Learn to detect and prevent subdomain takeover using AWS Config custom rules to identify dangling DNS CNAME records pointing to deleted resources in globally shared namespaces

Prevent data exfiltration: AWS egress controls for cloud workloads
Authors: Meriem Smache, Maxim Raya | Published: June 22, 2026
Learn to implement layered egress detection and protection using AWS Network Firewall, Amazon Route 53 Resolver DNS Firewall, and data perimeters to help reduce unauthorized data transfer risk.

Operationalizing AWS security: A maturity roadmap
Authors: Joseph Sadler | Published: June 8, 2026
A six-phase maturity roadmap for organizations that have already enabled AWS Security Hub and Amazon GuardDuty, covering tuning, notifications, automated remediation, and operational cadence.

Introducing AWS Continuum: Security at machine speed
Authors: Chet Kapoor | Published: June 17, 2026
AWS Continuum for code vulnerabilities is an AI-native platform that addresses the full lifecycle of a code vulnerability at machine speed—from discovery and prioritization through validation and remediation.

Accelerate security investigations with Kiro CLI
Authors: Sibasankar Behera, Marshall Jones | Published: June 18, 2026
Learn to use Kiro CLI to conduct security investigations following the AWS Security Incident Response Guide framework, from triaging Amazon GuardDuty findings through containment and evidence preservation.

What the June 2026 Threat Technique Catalog update means for your AWS environment
Authors: Shannon Brazil, Cydney Stude, Javier Teitelbaum | Published: June 29, 2026
Learn about five new entries and three updates to the Threat Technique Catalog for AWS, covering container security, organization-level trust, and compute hijacking patterns observed by AWS CIRT.

Identify unused AWS KMS keys and prevent accidental key deletions
Authors: Andrea Rossi, Poojil Tripathi | Published: June 2, 2026
Learn to use the new AWS KMS GetKeyLastUsage API to audit key activity, identify unused keys, and apply policy controls that prevent accidental deletion of recently used keys.

From Monolith to Multi-Account: Pinterest’s AWS Organization Transformation Journey
Authors: Sid Vantair, James Fogel, Jeremy Talis | Published: June 4, 2026
Learn how Pinterest migrated from a single monolithic AWS account to a multi-account architecture, including management account separation, automated account provisioning, and centralized networking.

Build a Multi Account Patch Compliance Dashboard with Kiro Specs
Authors: Justin Thomas | Published: June 9, 2026
Learn to use Kiro’s spec-driven development approach to build a serverless multi-account patch compliance dashboard with AWS Systems Manager Patch Manager and private access via AWS Systems Manager Session Manager.

Transfer AWS accounts between AWS Organizations while preserving AWS Lake Formation permissions
Authors: Alex Torres, Aarthi Srinivasan, Ryan McNamee | Published: June 12, 2026
Learn to migrate member accounts between AWS Organizations without disrupting AWS Lake Formation cross-account permissions by using temporary bridge shares with the new AWS RAM retention parameter.

Investigations of reported security vulnerabilities affecting Amazon and AWS services, software, and products.

• CVE-2026-10591 – Kiro IDE Insufficient File Write Restrictions to Execution-Sensitive Paths
• CVE-2026-10584 – HTTPS Fallback to HTTP in Graph Explorer
• CVE-2026-11400 and CVE-2026-11401 – Privilege Escalation in Aurora PostgreSQL using AWS Advanced JDBC Wrapper, AWS Advanced Go Wrapper
• CVE-2026-11393 – Code Injection via Improper Triple-Quote Escaping in AgentCore CLI Bedrock Agent Import
• CVE-2026-11417 – OS Command Injection in aws-cdk-lib NodejsFunction bundling
• CVE-2026-10740 – Excessive memory allocation in s2n-quic
• CVE-2026-12043 – Heap double-free in AWS Common Runtime aws-c-http
• CVE-2026-11931 – Insecure Permissions on Authentication Token Cache File in Kiro IDE
• CVE-2026-12530 – Improper neutralization of argument delimiters in AWS Bedrock AgentCore Python SDK install_packages()
• Issue with containerd CRI Plugin – CVE-2026-50195, CVE-2026-53488, CVE-2026-53492, CVE-2026-53489, CVE-2026-47262
• CVE-2026-12957 and CVE-2026-12958 – Issues in Language Servers for AWS and Amazon Q Developer Plugins
• CVE-2026-13762 and CVE-2026-13763 – Issue with HTTP/2 multi-frame request body inspection in AWS WAF

This month brings 10 new AWS samples spanning AI security, identity, infrastructure security, governance, and observability. From securing Amazon Bedrock AgentCore agents with AWS WAF to building graph-based CMDBs for dependency analysis, these repositories help you implement security and governance best practices across your AWS environment.

Securing Amazon Bedrock AgentCore Runtime with AWS WAF
Learn to place AWS WAF in front of Amazon Bedrock AgentCore Runtime using two architecture patterns with an Application Load Balancer and VPC endpoints for defense-in-depth protection.

AI Security Posture Management (AI SPM) on AWS
Learn to discover, assess, and protect AI agents running in your environment using AWS-native services across three pillars: observe, govern, and defend, with rules mapped to OWASP LLM Top 10, NIST AI RMF, and MITRE ATLAS.

Implement On-Behalf-Of (OBO) token exchange for Amazon Bedrock AgentCore agents
Learn to implement secure identity propagation from user context through agent chains using Amazon Bedrock AgentCore Identity OBO token exchange without credential sharing.

Monetizing AI traffic with Amazon CloudFront and AWS WAF (x402)
Learn to monetize AI traffic at the edge using AWS WAF native x402 protocol support with Amazon CloudFront, settling payments in a single round-trip with no Lambda@Edge required.

Turn repeatable processes into SOPs your AI agent works through one auditable step at a time
Learn to use this MCP server to hand standard operating procedures to your AI agent one step at a time, with gated execution and auditable progress tracking.

Bedrock Ops Lens
Learn to deploy an Amazon Bedrock observability dashboard in your own account for per-account, per-model, and per-tag cost attribution, quota tracking, latency monitoring, and model lifecycle management, with an MCP server for IDE access.

AWS Agent Registry sample demo application
Learn to use AWS Agent Registry to publish, review, approve, and discover AI agents, MCP servers, and agent skills through a centralized catalog with governance workflows.

Graph CMDB — an AWS resource relationship graph
Learn to build a graph-based CMDB from AWS Config, AWS IAM, Amazon EKS, AWS CloudTrail, and VPC Flow Logs to visualize resource dependencies, investigate scope of impact, and surface governance findings.

OpenAI Codex through Amazon Bedrock — Usage governance with LiteLLM
Learn to centrally govern, administer, and monitor OpenAI Codex access for engineering teams using Amazon Bedrock as the inference backend with per-user budgets, rate limits, and audit trails via LiteLLM.

Agentic Data Governance — the context ladder
Learn to measure how governance context layers — data dictionaries, semantic metrics, and execution skills — improve data agent accuracy through a four-level ablation ladder on the BIRD benchmark.

June 2026 provides guidance and examples for operationalizing security at organizational scale; from maturity roadmaps and console access restrictions to AI agent registries and posture management platforms. The posts and samples provide patterns for DDoS visibility with flow logs, multi-tenant agent isolation with resource-based policies, egress controls for data exfiltration prevention, and governance frameworks for AI coding assistants. Each resource includes deployment steps or runnable code so you can validate in your own environment before adopting. Subscribe to the AWS Security Blog RSS feed to receive updates as they publish, and revisit this digest monthly for a consolidated view of what changed and what to act on.

If you have feedback about this post, submit comments in the Comments section below.

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We are pleased to announce the publication of a new AWS compliance implementation guidance: HITRUST i1 Compliance on AWS: Customer Implementation Guidance with an Illustrative Healthcare Platform.

Healthcare organizations seeking HITRUST i1 certification increasingly rely on Amazon Web Services (AWS) as their cloud foundation. The HITRUST i1 assessment covers 182 curated controls at the Implemented level and is the most widely required HITRUST certification tier in healthcare vendor contracts and Business Associate Agreements required by health plans, hospital systems, and business associates as a condition of working with them.

This guide is designed to close the gap between understanding what HITRUST i1 requires and knowing how to implement it on AWS. It walks cloud architects, security engineers, compliance leads, and assessment preparation teams through the full lifecycle of an i1 engagement from defining the assessment boundary to implementing controls across each technical domain.

What the guide covers

The guide addresses 11 HITRUST i1 technical control domains, with supporting AWS implementation components relative to these domains. The domains include access control, endpoint protection, configuration management, vulnerability management, network protection, transmission protection, incident management, data protection and privacy, audit logging and monitoring, password management, and business continuity and disaster recovery.

The guidance is grounded in a fictional but realistic connected healthcare platform deployed on AWS Landing Zone Accelerator. The scenario is used to make abstract HITRUST concepts concrete, not to suggest that the same architecture or control choices apply universally. HITRUST i1 scoping is inherently organization-specific. The assessment boundary, applicable controls, and evidence requirements are determined by each organization’s system scope and delivered through the HITRUST MyCSF portal. Readers should treat the guidance as a starting point and work with a HITRUST Authorized External Assessor to validate what applies to their specific environment. This guide doesn’t constitute a compliance certification advisory.

Getting started

You can download the guide here: HITRUST i1 Compliance on AWS: A Customer Implementation Guidance with an Illustrative Healthcare Platform.

AWS HITRUST assurance documentation and the Customer Responsibility Matrix are available through AWS Artifact. For assessment readiness support, visit AWS Security Assurance Services.

If you have feedback about this post, submit comments in the Comments section below.

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Amazon Web Services EMEA Sarl (AWS) has been designated as a critical third party (CTP) to the UK financial sector by HM Treasury.

The CTP regime came into force on January 1, 2025, and establishes a framework through which the Bank of England, PRA, and FCA (collectively the UK regulators) can set requirements on and have direct oversight of designated CTPs.

AWS supports the objectives of the UK regulators to ensure a robust financial system.

AWS obligations under the regime

The CTP regime is an outcomes-focused framework. Under the regime, AWS will be subject to requirements in relation to its designated Systemic Third-Party Services (STPS). The first step will be a self-assessment of these STPSs against the CTP regime criteria, which AWS will now carry out in line with regulators’ expected timelines.

AWS has actively engaged with the UK authorities as they’ve developed the CTP regime, and we will continue this constructive approach as we work to meet our obligations under it.

Impact on customers

The UK regulators have clarified that the requirements under the regime don’t eliminate, reduce, or replace the accountability of firms, their boards, and senior management for remaining operationally resilient, including when they rely on services provided by third parties.

The regime doesn’t change obligations on financial services customers of designated CTPs. As we manage our obligations, we expect to publish materials that customers can use to inform their own operational resilience planning and third-party risk management.

The AWS commitment to operational resilience

We’re focused on supporting financial services customers in enhancing their operational resilience and providing a range of services and guidance—including the AWS Well-Architected Framework and resources for cloud incident management—to help organizations deliver effective resilience outcomes.

AWS has a team of regulatory and technology experts with expertise in financial services ready to support customers with questions about this regime or operational resilience more broadly. Customers can contact their AWS account team for further information.

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Amazon Web Services (AWS) is excited to release the Spring 2026 System and Organization Controls (SOC) 1 and 2 reports in machine-readable OSCAL format alongside the PDF version of the reports. The reports cover 188 services over the 12-month period from April 1, 2025 to March 31, 2026, giving customers a full year of assurance. These reports demonstrate our continuous commitment to adhering to the heightened expectations of cloud service providers.

AWS is the first major cloud provider to offer key compliance reports to customers in the National Institute of Standards and Technology’s (NIST) Open Security Controls Assessment Language (OSCAL), as of June 2026. OSCAL is an open source, machine-readable (JSON) format for security information. The SOC 1 and SOC 2 report package in OSCAL format is now available as a distinct package in AWS Artifact, marking a milestone toward open, standards-based compliance automation. This machine-readable version of the SOC report package enables workflow automation to reduce manual processing time and modernize security and compliance processes. Your use cases for this content are innovative, and we want to hear about them through the contact information found in the OSCAL report package.

You can download the Spring 2026 SOC 1 and 2 reports in OSCAL format through AWS Artifact, a self-service portal for on-demand access to AWS compliance reports. Sign in to AWS Artifact in the AWS Management Console, or learn more at Getting Started with AWS Artifact. The SOC 3 report can be found on the AWS SOC Compliance page and in AWS Artifact.

AWS strives to continuously bring services into the scope of its compliance programs to help customers meet their architectural and regulatory needs. You can view the current list of services in scope on our Services in Scope page. As an AWS customer, you can reach out to your AWS account team if you have any questions or feedback about SOC compliance.

To learn more about AWS compliance and security programs, see AWS Compliance Programs.

What we believe

We’ve been thinking deeply about enterprise security. The operating model that served us for the past decade (collect telemetry, store it, query it, build dashboards to watch it) is no longer keeping pace. We need to shift to the new world: telemetry, context, reasoning, and actions. An approach that produces outcomes. The latest cybersecurity frontier models further made this shift urgent. Models like Claude Mythos can now find software vulnerabilities and reason through complex attack paths at machine-speed, leading to an exponentially increasing backlog of vulnerabilities.

Introducing AWS Continuum for code vulnerabilities

Today, we’re announcing AWS Continuum for code vulnerabilities, now available in gated preview. Continuum for code vulnerabilities addresses the full lifecycle of a code vulnerability at machine speed: from discovery through actions. It reasons over your environment, confirms what is real, and drives toward resolution. It’s model agnostic, using multiple frontier models where each performs best, and is built to incorporate the latest and most capable models as they emerge.

Continuum is built on lessons learned from running security across AWS and Amazon.com. Securing businesses that operate in different industries required a system that understands business context rather than applying generic rules uniformly.

How it works

Continuum for code vulnerabilities reasons over your full environment. This context includes structured data already living in Amazon Web Service (AWS) (your infrastructure, permissions, network topology, code) and the unstructured data that captures how your organization operates and your risk profile (your documents, communications, business priorities).

Continuum for code vulnerabilities operates in four continuous phases.

1. Discovery: Security teams tackle a backlog of vulnerabilities, and many are already using frontier models to find more. Continuum starts by ingesting that existing backlog and performing its own vulnerability scan of your environment. This creates a more comprehensive view of vulnerabilities and the associated attack paths.
2. Prioritization: Continuum uses context to evaluate, enrich, and prioritize every finding. Is the affected component deployed, is it reachable, is it in a production path, and what would the business impact be if exploited? The result is an evidence-backed list of priorities, allowing Continuum and your team to focus on what’s most important.
3. Validation: Continuum validates findings to surface false positives before they waste your team’s time. It contextualizes vulnerabilities against your environment. It then constructs working exploit examples in a sandboxed environment that provide concrete, reproducible evidence of the issue.
4. Mitigation and remediation: Continuum assesses existing defenses around a validated issue, including blocking and compensating controls along with detection mechanisms. It then draws on its understanding of the codebase, context, and findings to recommend mitigation or remediation of the vulnerability with a network change, policy change, or code patch. The patch recommendation is validated using the same system that confirmed the vulnerability. It also provides blast radius visibility and rollback paths where feasible.

This is just the beginning. We’re starting with code (1^st and 3^rd party) and then expanding to other aspects of security.

Trust is graduated

Continuum starts in learn mode with a human in the loop. Every recommendation includes the reasoning behind it. As you gain confidence, you can graduate Continuum to enforce mode, enabling remediation that can be increasingly automated based on categories and risk profiles you define.

Continuum capabilities

In addition to Continuum for code vulnerabilities, Continuum includes capabilities you might already know. The AWS Security Agent penetration testing and code scanning functionality is now part of Continuum as Continuum pen testing and Continuum code scanning (Preview). We’re also launching Continuum threat modeling in preview, which automatically generates comprehensive threat models from design documents or source code and outputs results in STRIDE format. These capabilities serve as detection and analysis sources that feed into the broader Continuum loop of discovery, prioritization, validation, and remediation.

Getting started

We’re working with customers across financial services, automotive, and technology to shape AWS Continuum. Customer feedback confirms the direction: security teams want tools that earn trust and take action.

AWS Continuum for code vulnerabilities is available in gated preview. Sign up to request access at AWS Continuum.

If you have feedback about this post, submit comments in the Comments section below.

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Read all about the latest AWS security features, compliance updates, and hands-on resources in our new, monthly digest posts. You’ll find expert blog posts, new service capabilities, code samples, and workshops.

This month’s AWS Security Blog posts covered AI security, network protection, identity management, compliance frameworks, and supply chain security. Read on for practical guidance on securing agentic AI workflows, filtering network traffic by category, defending against supply chain attacks, and more.

Security posture improvement in the AI era
Author: Celeste Bishop | Published: May 1, 2026
Learn to use the Security Health Improvement Program (SHIP) to strengthen security fundamentals across 10 core use cases for confident AI adoption.

Enabling AI sovereignty on AWS
Author: Stéphane Israël | Published: May 12, 2026
Learn how AWS delivers control and choice across the AI stack to help customers meet digital and AI sovereignty requirements.

The AWS AI Security Framework: Securing AI with the right controls, at the right layers, at the right phases
Authors: Riggs Goodman III, Christopher Rae | May 15, 2026
A structured framework that helps security leaders align the right security controls to the right AI use case, at the right layer, at the right deployment phase.

Why Policy in Amazon Bedrock AgentCore chose Cedar for securing agentic workflows
Authors: Liana Hadarean, Jean-Baptiste Tristan | May 20, 2026
Learn how Cedar’s deterministic authorization, automated reasoning, and formal verification capabilities secure agentic AI tool invocations through Amazon Bedrock AgentCore Gateway.

Securing open proxies in your AWS environment
Author: Dodd Mitchell | Published: May 4, 2026
Learn to identify and secure open proxies in your AWS environment to prevent abuse, protect your IP reputation, and control costs.

Introducing AI traffic analysis dashboards for AWS WAF
Authors: Christopher Jen, Eitav Arditti, Kaustubh Phatak | Published: May 5, 2026
A new dashboard providing visibility into AI bot and agent activity including bot identification, intent classification, and access pattern analysis.

Simplifying policy management with URL and Domain Category filtering on AWS Network Firewall
Authors: Lawton Pittenger, Sofía Aluma-Santos, Eric Fortenbery, Mostafa Elkhouly | May 28, 2026
Learn to use AWS Network Firewall’s URL and domain category filtering to control access to website categories like AI services, manage exceptions for approved domains, and monitor traffic patterns with Amazon CloudWatch Logs Insights.

Why and how to migrate to a Transit Gateway-attached AWS Network Firewall
Authors: Frank Phillis, Lawton Pittenger | May 28, 2026
Learn to migrate your centralized AWS Network Firewall deployment to a AWS Transit Gateway-attached model, eliminating the inspection Amazon VPC and enabling flexible cost allocation.

Regional routing for AWS access portals: Implementing custom vanity domains for IAM Identity Center
Authors: Georgi Baghdasaryan, Laura Reith, Sowjanya Rajavaram | May 14, 2026
Learn to build a custom vanity domain with latency-based routing and automated failover for IAM Identity Center multi-Region access portals.

Automating identity lifecycle and security with AWS Directory Service APIs
Authors: Ali Alzand, Kevin Sookhan | May 21, 2026
Learn to use the new AWS Directory Service Data APIs with Amazon GuardDuty and AWS Step Functions to automate identity lifecycle management and respond to security threats.

Announcing the ISO 31000:2018 Risk Management on AWS compliance guide
Authors: Jesse McMahan, Akanksha Chaturvedi, Mayur Jadhav, Juan Rodriguez, Sana Rahman | Published: May 1, 2026
A compliance guide providing practical guidance for establishing a risk management program using ISO 31000:2018 principles in AWS environments.

New compliance guide available: ISO/IEC 42001:2023 on AWS
Authors: Abdul Javid, Amber Welch, Muhammad Sharief, Jonathan Jenkyn, Satish Uppalapati | Published: May 6, 2026
A compliance guide providing practical guidance for designing and operating an Artificial Intelligence Management System (AIMS) using AWS services.

Introducing the updated AWS User Guide to Governance, Risk, and Compliance for Responsible AI Adoption
Authors: Krish De, Stephen James Martin, Brenda Fong, Kelvin Leung | May 13, 2026
An updated guide providing FSI customers practical considerations for responsible AI adoption across governance, risk management, compliance, data management, and AI agent management.

Governing infrastructure as code using pattern-based policy as code
Authors: Guptaji Teegela, Paul Keastead | May 19, 2026
Learn to use Open Policy Agent (OPA) in CI/CD pipelines to validate AWS infrastructure changes before deployment using recurring control patterns.

Import historical data from AWS CloudTrail Lake to Amazon CloudWatch
Authors: Isaiah Salinas, Erik Weber|Published: May 6, 2026
Learn to import historical data from AWS CloudTrail Lake into Amazon CloudWatch for centralized log analysis.

Automating post-quantum cryptography readiness using AWS Config
Author: Pravin Nair | May 14, 2026
Learn to use the PQC Readiness Scanner to inventory your ALB, NLB, and Amazon API Gateway endpoints and continuously monitor their TLS configurations for post-quantum cryptography readiness.

Detecting and preventing crypto mining in your AWS environment
Authors: Jason Palmer, Nadia Mahmood | May 13, 2026
Learn to use Amazon GuardDuty to identify and mitigate cryptocurrency mining threats in your AWS environment with a multi-layered defense strategy.

Well-architected best practices for software supply chain security
Authors: Trevor Schiavone, Desiree Brunner | May 26, 2026
Learn to apply AWS Well-Architected Framework security best practices to defend against software supply chain attacks like Shai-Hulud using temporary credentials, centralized dependency management, artifact signing, and continuous scanning.

AWS Security Hub Extended: Why enterprise security products should sell themselves
Author: Michael Fuller | May 20, 2026
A thought leadership piece on how AWS Security Hub Extended enables frictionless, pay-as-you-go adoption of curated partner security solutions alongside AWS-native services.

Five ways to use Kiro and Amazon Q to strengthen your security posture
Author: Roger Nem | Published: May 5, 2026
Learn to use Kiro and Amazon Q Developer for security finding triage, infrastructure remediation, security reviews, and service control policies (SCP) development.

AWS Security Agent full repository code scanning feature now available in preview
Authors: Ayush Singh, Daniele Bonadiman | May 12, 2026
Learn to use AWS Security Agent’s full repository code review to perform deep, context-aware security analysis of your entire code base.

Complimentary virtual training: Get hands-on with AWS Security services
Author: Ashley Nelson | Published: May 11, 2026
Security Activation Days are free 3–6 hour virtual workshops providing hands-on practice with AWS security services guided by specialists.

Investigations of reported security vulnerabilities affecting Amazon and AWS services, software, and products.

• Ongoing updates on Copy.fail and variants
• CVE-2026-7791 – Local Privilege Escalation via TOCTOU Race Condition in Amazon WorkSpaces Skylight Agent
• CVE-2026-8178 – Remote Code Execution via Unsafe Class Loading in Amazon Redshift JDBC Driver
• CVE-2026-8596 & CVE-2026-8597: Issue with Amazon SageMaker Python SDK – Model artifact integrity verification issues
• CVE-2026-8686 – Heap out-of-bounds read in coreMQTT MQTT5 property parsing
• CVE-2026-8838 – Remote Code Execution in amazon-redshift-python-driver
• CVE-2026-9133 – Arbitrary file read in rabbitmq-aws plugin
• CVE-2026-9255 – Tool Execution Without Authorization via Piped Stdin in Kiro CLI
• CVE-2026-9291 – Insecure Deserialization in Amazon Braket SDK Job Results Processing
• CVE-2026-10591 – Kiro IDE Insufficient File Write Restrictions to Execution-Sensitive Paths
• CVE-2026-10584 – HTTPS Fallback to HTTP in Graph Explorer

This month brings 8 new AWS samples spanning application security, data protection, infrastructure security, governance, and AI security. From AI-powered security agents on Amazon Bedrock AgentCore to centralized AWS Config monitoring at scale, these repositories help you implement security best practices across your AWS environment.

Schedule AWS Security Agent penetration test
Learn to deploy a AWS CloudFormation template that uses Amazon EventBridge and AWS Step Functions to schedule recurring AWS Security Agent penetration tests with Amazon Simple Notification Service
(SNS) notifications on completion.

Security review assistant
Learn to deploy a multi-agent system on Amazon Bedrock AgentCore that automates Deliverable Security Reviews by combining architecture analysis, IaC code review, ASH vulnerability scanning, and compliance assessment into a single pipeline.

AWS Security Agent Recorder
Learn to use a cross-browser extension that records the unique domains your web app contacts and auto-fills them into the AWS Security Agent penetration test configuration.

KMS access audit
Learn to resolve and report who can use your AWS Key Management Service (KMS) keys across IAM policies, key policies, and grants, with IAM Identity Center resolution to identify the humans behind SSO roles.

Building a conversational AI agent for AWS WAF analysis with AgentCore
Learn to deploy an AI-powered agent using Amazon Bedrock AgentCore and Strands SDK that investigates AWS WAF security incidents, detects bypasses, and generates security reports through natural language.

Centralized AWS Config CI monitoring with Amazon CloudWatch
Learn to centrally monitor AWS Config Configuration Item recording across all accounts in an AWS Organization using CloudWatch Cross-Account Observability, with dashboards showing top resource types, per-account volume, and conformance pack compliance.

CloudFormation Guard security analyzer
Learn to deploy an AI agent powered by Amazon Bedrock AgentCore that scans CloudFormation resource documentation, identifies security-critical properties with risk levels, and generates ready-to-use cfn-guard 3.x rules for your CI/CD pipeline.

Guarded user-controlled attested runtime deployment (Guardian Platform)
Learn to deploy LLM models securely in consumer AWS accounts while protecting model weights using AWS Nitro TPM attestation, KMS envelope encryption, and Zero Operator Access with immutable AMIs.

This month brings 1 new AWS Labs repository focused on governance, helping research institutions deploy secure, tagged infrastructure with self-service access and multi-account controls.

ResearchStack on AWS
Learn to deploy research computing infrastructure on AWS in minutes — Amazon EC2, S3, EFS, Amazon SageMaker AI, and ParallelCluster — with built-in security, cost tracking, and governance using CloudFormation templates and optional AWS Service Catalog.

May 2026 shows AI security maturing from model-level controls to full-stack protection of agentic workflows. The posts and samples provide patterns for policy-based authorization with Cedar, network traffic filtering by category, and cross-account compliance monitoring. The security bulletins address vulnerabilities in SDKs, drivers, and developer tooling. Each resource includes deployment steps or runnable code so you can validate in your own environment before adopting. Subscribe to the AWS Security Blog RSS feed to receive updates as they publish, and revisit this digest monthly for a consolidated view of what changed and what to act on.

If you have feedback about this post, submit comments in the Comments section below.

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Amazon Web Services (AWS) is pleased to announce that the Spring 2026 System and Organization Controls (SOC) 1, 2, and 3 reports are now available. The reports cover 188 services over the 12-month period from April 1, 2025–March 31, 2026, giving customers a full year of assurance. These reports demonstrate our continuous commitment to adhering to the heightened expectations of cloud service providers.

Customers can download the Spring 2026 SOC 1 and 2 reports through AWS Artifact, a self-service portal for on-demand access to AWS compliance reports. Sign in to AWS Artifact in the AWS Management Console, or learn more at Getting Started with AWS Artifact. The SOC 3 report can be found on the AWS SOC Compliance Page and AWS Artifact.

AWS strives to continuously bring services into the scope of its compliance programs to help customers meet their architectural and regulatory needs. You can view the current list of services in scope on our Services in Scope page. As an AWS customer, you can reach out to your AWS account team if you have any questions or feedback about SOC compliance.

To learn more about AWS compliance and security programs, see AWS Compliance Programs.

If you have feedback about this post, submit comments in the Comments section below.

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May 26, 2026: This post was originally published in July 2022. It has been updated to reflect current engagement options, new threat intelligence resources such as the Threat Technique Catalog for AWS (TTC), additional open-source tools, and the distinction between AWS CIRT support and the AWS Security Incident Response managed service.

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Welcome back, or welcome for the first time. Either way, we’re glad you’re here. We’re the AWS Customer Incident Response Team (CIRT), and we want to share who we are and how we can help when it matters most.

The AWS CIRT is a specialized 24/7 global team within Amazon Web Services (AWS) that provides support to customers during active security events on the customer side of the AWS Shared Responsibility Model. Our team is made up of security engineers who respond to cloud security events and build the tools and resources we use to do it.

Important: If you’re experiencing an active security event in your AWS environment—such as unauthorized access, data exfiltration, or ransomware—open an AWS support case and request assistance.

To request assistance from AWS:

1. Open a support case from the impacted AWS account through the AWS Support Center Console.
2. Select the service most closely related to the security event (for example, Amazon Elastic Compute Cloud (Amazon EC2), AWS Identity and Access Management (IAM), Amazon Simple Storage Service (Amazon S3)).
3. Mention that you have an urgent security incident in the case description.

Opening a support case from the affected account allows AWS to confirm account ownership and gives you a case number to track the engagement. If you have an account team (TAM, Account Manager, or Solutions Architect), you can also alert them to initiate an escalation.

If you’ve lost access to your account, you can still submit a request for assistance.

When the AWS CIRT supports you, we focus on investigating security events as they appear in AWS service logs and the AWS control plane. For our analysis, we draw on sources such as AWS CloudTrail, Amazon VPC Flow Logs, and Amazon GuardDuty findings. We assist with triage, analysis, and containment, alongside providing recommendations and best practices to help you avoid security events in the future.

The AWS CIRT works alongside AWS threat intelligence and security operations teams. During an engagement, we use current threat intelligence and AWS infrastructure knowledge to inform our analysis and recommendations.

For investigations that extend into host-level or application-level analysis—such as operating system forensics, memory analysis, or application code review—we recommend complementing our support with a specialized AWS Partner for digital forensics and incident response (DFIR) capabilities.

Figure 1 shows the two different sides of the shared responsibility model, in which AWS is responsible for security OF the cloud, while customers are responsible for security IN the cloud.

The AWS CIRT regularly encounters patterns that repeat across our engagements. The TTC started as an internal reference—a way for our team to track and share what we were seeing across engagements, so we weren’t solving the same problems in isolation. Over time, it became clear that the knowledge we were building for ourselves was exactly what customers needed to get ahead of the same threats. So, we made it public. When we see techniques repeating across customers, an effective way to help them is to document those techniques and make that knowledge available so they can act on it before they’re in the middle of an incident.

To that end, we developed the Threat Technique Catalog for AWS (TTC)—a publicly available catalog, based on MITRE ATT&CK Cloud Matrix, that documents threat actor tactics, techniques, and procedures (TTPs) specific to AWS as observed by the AWS CIRT. Each entry includes detection guidance and mitigations specific to AWS environments. You can filter for the AWS services in your account to focus on what’s most relevant to you.

Findings from the TTC also inform detection logic in AWS services like Amazon GuardDuty, helping customers strengthen automated protections in their environments.

We’ve open-sourced several tools based on patterns we see in engagements. These complement rather than replace your existing security tooling. For a comprehensive framework for building your incident response program, see the AWS Security Incident Response Guide.

The tools below started as internal solutions we built to solve problems we kept running into.

• AWS Customer Playbook Framework – Publicly available response frameworks that use our lessons learned from security events
• Assisted Log Enabler – A tool that assists customers to enable logs, including the following: Amazon VPC Flow Logs, AWS CloudTrail, Amazon Elastic Kubernetes Service (Amazon EKS) audit and authenticator logs, Amazon Route 53 Resolver Query Logs, Amazon Simple Storage Service (Amazon S3) server access logs, and Elastic Load Balancing logs
• AWS CloudSaga – A tool for testing security controls and alerts within an AWS environment by using generated simulated events based on common security events seen by the AWS CIRT
• Athena Security Analytics Bootstrap – A tool for customers who need a quick method to set up Amazon Athena and perform investigations on AWS service logs archived in S3 buckets

We maintain five publicly available workshops, regularly updated to simulate current security events to help you learn tools and procedures that we use daily. The workshops cover unauthorized IAM credential use, ransomware on Amazon S3, cryptomining, SSRF on IMDSv1, and incident response preparedness tooling. All you need is an AWS account, an internet connection, and the desire to learn more about incident response in the AWS Cloud. These workshops are built using the same scenarios our team trains on internally—we wanted to make that accessible to everyone.

Any AWS customer can engage the AWS CIRT through an AWS support case, regardless of support plan level. For those customers who have an account team, you can start an escalation to the AWS CIRT with the account team. Customers with Enterprise Support or Unified Operations can also onboard to AWS Security Incident Response, a managed service for security event triage and response.

Thank you for reading. This post is where we share what we’re learning—security trends, new resources, and threat intelligence—so you can stay prepared. If you’ve worked with us and have thoughts on how we can do better, reach out through your AWS account team, the comments below, or aws-cirt@amazon.com.

Until next time: logs on, credentials rotated, and alerts reviewed.

We also recommend subscribing to AWS Security Bulletins for notifications about security events for AWS services. You can subscribe through RSS feed to stay informed.

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We’re excited to announce that Amazon Web Services (AWS) has completed the S&P Global Know Your Third Party (KY3P) assessment of its security posture. This assessment demonstrates our continued commitment to meet the heightened expectations of cloud service providers. Customers can now use the AWS KY3P assessment to reduce their supplier due diligence burden.

KY3P, also known as the S&P Global Comprehensive Assessment (formerly TruSight), is a validated, evidence-based assessment designed to support regulatory compliance and efficient, standardized risk data exchange between AWS and our clients. KY3P’s globally recognized methodology provides organizations with enhanced visibility into supply chain risks by validating the actual implementation and operation of controls – not just policies or attestations.

As cloud adoption accelerates across industries, AWS has become a critical component of customers’ third-party environments. Regulated customers, such as those in the financial services sector, are held to high standards by regulators and auditors when it comes to exercising effective due diligence on third parties.

To better manage risks from their evolving third-party environments and drive operational efficiencies, many customers rely on third-party risk management services such as KY3P. In support of these efforts, AWS has completed its annual KY3P security posture assessment, conducted by KY3P security assessors.

KY3P’s risk assessment methodology includes over 200 controls across 26 control categories and nine risk domains. These topics include Privacy, Network Management, Logical Access Management, and Physical and Environmental Security. The assessment criteria were developed by a consortium of leading financial institutions.

Customers can use the KY3P results to map AWS against commonly used industry frameworks and standards, such as NIST CSF v2, PCI DSS 4.0, and ISO 27001:2022 to instantly gain visibility into controls coverage.

For details on how to access the report, see our AWS KY3P assessment page.

If you have feedback about this post, submit comments in the Comments section below. To learn more about our other compliance and security programs, see AWS Compliance Programs.

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 navigate these challenges, AWS is excited to announce an updated AWS User Guide to Governance, Risk, and Compliance for Responsible AI Adoption within Financial Services Industries.

This comprehensive guide provides FSI customers practical considerations for responsible AI adoption across key dimensions including governance, risk management, compliance, data management, model management and AI agent management. It includes detailed AWS service capabilities that customers can use to address these considerations, such as Amazon Bedrock AgentCore, Amazon Bedrock Guardrails, Amazon Bedrock Agents, Amazon SageMaker Autopilot, and Amazon SageMaker Model Monitor.

The guide is available at the AWS Whitepaper portal and is complementary to other AWS resources such as the AWS Responsible Use of AI Guide, AWS Cloud Adoption Framework for AI, AWS Well-Architected Framework – Responsible AI Lens, AWS Well-Architected Framework – Generative AI Lens, and AWS Well-Architected Framework – Machine Learning Lens.

As the regulatory environment and leading practices continue to evolve, we will provide further updates on the AWS Security Blog and AWS Compliance Center. You can also reach out to your AWS account team for help finding the resources you need.

Resources

• AWS Cloud Security
• AWS Compliance
• AWS Security Reference Architecture
• Best Practices for Security, Identity, & Compliance
• Data Protection at AWS
• Zero trust on AWS
• Cryptographic Computing

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

Amazon Web Services (AWS) is pleased to announce the successful completion of Payment Card Industry Personal Identification Number (PCI PIN) and PCI Point-to-Point Encryption (PCI P2PE) assessments for the AWS Payment Cryptography service. This assessment expands the AWS Payment Cryptography compliance portfolio, with AWS now validated as a component provider for Key Management (KMCP) and Key Loading (KLCP) in addition to the existing Decryption Management (DMCP) attestation, and extends PCI PIN and P2PE coverage to the South America (São Paulo) and Asia Pacific (Sydney) AWS Regions.

With Payment Cryptography, your payment processing applications can use payment hardware security modules (HSMs) that are PCI PIN Transaction Security (PTS) HSM certified and fully managed by AWS, with PCI PIN and P2PE-compliant key management. These attestations give you the flexibility to deploy your regulated workloads with reduced compliance overhead.

The PCI P2PE Decryption Component enables payment applications to use AWS to decrypt credit card transactions from payment terminals, and PCI PIN attestation is required for applications that process PIN-based debit transactions. The PCI P2PE Key Management and Key Loading Component attestations enable applications to use AWS for physical key exchange and to support key management use cases including key injection. To learn more about the new Physical Key Exchange feature, see the AWS What’s New announcement. With these capabilities, AWS Payment Cryptography enables customers to manage cryptographic keys in accordance with PCI standards and industry best practices, reducing the operational burden of maintaining compliant key management infrastructure.

The PCI PIN and PCI P2PE compliance packages for AWS Payment Cryptography includes the following reports:

• PCI PIN Attestation of Compliance (AOC) – Demonstrates that AWS Payment Cryptography was successfully validated against the PCI PIN standard with zero findings
• PCI PIN Responsibility Summary – Provides guidance to help AWS customers understand their responsibilities in developing and operating a highly secure environment for handling PIN-based transactions
• PCI P2PE DMCP Attestation of Validation (AOV) – Demonstrates that AWS Payment Cryptography was successfully validated against the requirements for a PCI P2PE Decryption Management System with zero findings
• PCI P2PE KMCP Attestation of Validation (AOV) – Demonstrates that AWS Payment Cryptography was successfully validated against the requirements for a PCI P2PE Key Management Component Provider with zero findings
• PCI P2PE KLCP Attestation of Validation (AOV) – Demonstrates that AWS Payment Cryptography was successfully validated against the requirements for a PCI P2PE Key Loading Component Provider with zero findings
• P2PE Component User’s Guide and Annual Component Report – Describes the AWS Payment Cryptography service assessment scope as a PCI P2PE Decryption Component, Key Loading Component, and Key Management Component and illustrates PCI P2PE compliance responsibilities for both the service and customers using the service for point-to-point encryption processing

AWS was evaluated by Coalfire, a third-party Qualified Security Assessor (QSA). Customers can access the PCI PIN Attestation of Compliance (AOC) report, the PCI PIN Shared Responsibility Summary, the PCI P2PE Attestation of Validation, and P2PE Decryption Component User’s Guide and Annual Decryption Component Report through AWS Artifact.

To learn more about our PCI programs and other compliance and security programs, visit the AWS Compliance Programs page. As always, we value your feedback and questions; reach out to the AWS Compliance team through the Compliance Support page.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

Today, we’re excited to announce the preview release of full repository code review, a new capability in AWS Security Agent that performs deep, context-aware security analysis of your entire code base. AI-driven cybersecurity capabilities are advancing rapidly. AWS Security Agent can now find vulnerabilities and build working exploits across your entire code base at a scale and speed we haven’t seen before, reasoning like a human security researcher, but operating at machine velocity. Unlike traditional static analysis tools that match code against known vulnerability patterns, full repository code review reasons about your application’s architecture, trust boundaries, and data flows the way a human security researcher would and then produces developer-ready findings with transparent evidence and concrete remediation.

AWS is prioritizing free early access for customers, giving defenders the opportunity to strengthen their code bases and share what they learn so the whole industry can benefit.

Development teams today face persistent tension. Traditional static application security testing (SAST) tools are fast and reliable at catching known patterns such as a SQL injection sink, an unescaped output, or a hard-coded credential. But modern applications are complex systems of services, APIs, trust boundaries, and authorization logic. The most dangerous vulnerabilities often aren’t single-line pattern violations, rather they’re systemic gaps where a validation function covers four of five cases, one endpoint is missing the authorization annotation its neighbors have, or encoding is applied in one context but not another.

Manual security reviews catch these issues, but they’re expensive, slow, and don’t scale to the pace of modern development. As code bases grow, teams are forced to choose between breadth and depth.

Full repository code review is built to close this gap. It gives your team an automated security researcher that reads and reasons about your entire repository, not just individual lines or file, and surfaces findings that pattern-matching tools miss.

Full repository code review operates in four stages that mirror how an experienced security engineer conducts an engagement.

1. Profile the application: The scanner begins by reading the entire repository and building a security model of the application including entry points, trust boundaries, data flows, authorization invariants, and the defenses already in place. This profiling step accounts for every source file, so coverage decisions are explicit rather than implicit. The result is a structured understanding of what the application does and where its attack surface lies.

2. Search for vulnerabilities: An orchestrator reads the security profile, reasons about the attack surface, and dispatches specialized agents to the highest-risk components. Each agent receives a scoped assignment with specific modules, threat context, and adversarial questions. Agents are free to follow imports and callers beyond their starting scope when a lead takes them there.

3. Triage and deduplicate: Candidate findings are deduplicated (same sink, same root cause) and low-confidence noise is filtered out before the validation phase.

4. Validate independently: For every candidate, an independent validator re-reads the source code and traces the full attack chain. The validator argues both sides: it looks for reasons the finding might not be a vulnerability (compensating controls, intentional design), and it looks for reasons it is one (alternative attack paths, edge cases). A finding is only rejected when the evidence against it is as strong as the evidence that promoted it. This process produces findings with structured Verified and Could not verify sections, so your team knows exactly what the scanner confirmed in the code and what depends on your deployment environment.

Full repository code review differs from traditional static analysis in two fundamental ways. It reasons about your application’s actual behavior rather than matching against known vulnerability patterns, and it presents findings with structured evidence that makes uncertainty explicit rather than hidden.

Because the scanner builds a security model before searching for vulnerabilities, it reasons about the application’s actual behavior, not only surface-level code patterns.

Consider a real example: A stored procedure had a SQL injection vulnerability. A traditional SAST tool would flag the specific EXECUTE IMMEDIATE call. The scanner went deeper and it identified that the central validation function doesn’t block single quotes in any of its five regex profiles, listed all five profiles by name, explained why single quotes matter for the specific database engine, and noted that another stored procedure skips the validation function entirely. Instead of a point fix on one call site, the finding led to a comprehensive remediation of the systemic gap.

In another case, the scanner found an XSS vulnerability where a value was added to a field without HTML encoding. The same value was properly encoded with Encode.forHtml() in a different context within the same file. Pattern-matching tools miss this because the encoding function is present, but the vulnerability is the inconsistency, which requires understanding the application’s behavior across code paths.

Every finding is structured for efficient developer triage:

• Problem: What the code does wrong, with specific file and line references.
• Impact: What an attacker gains, with details about deployment context.
• Verified and could not verify: What the scanner confirmed directly in code versus what depends on your environment (network segmentation, runtime behavior).
• Remediation: Concrete fix suggestions with specific code changes, not generic guidance.
• Severity and confidence: Calibrated independently. Severity reflects the impact if the vulnerability is exploitable; confidence reflects how much of the attack chain was verified in code.

Full repository code review is designed to complement, not replace, your existing security tooling. Here’s how it fits into a modern development workflow:

• Before security reviews: Run a full repository code review before scheduling a penetration test or security review. The review surfaces the obvious and semi-obvious issues so your security team can focus their limited time on the subtle, design-level questions that require human judgment.
• When onboarding acquired or open source code: Full repository code review is especially valuable when your team inherits code through acquisitions or vendor dependencies, or from open source components you’re integrating. The scanner builds a security model from scratch, so it doesn’t need institutional knowledge of the codebase.
• During architecture reviews: Because the scanner reasons about trust boundaries, data flows, and authorization invariants, its findings often surface architectural issues, not only implementation bugs. Review the scan results alongside your threat models to validate assumptions about how components interact.

Follow our Quickstart guide to set up and execute a full repo code review with AWS Security Agent.

Full repository code review is available today in preview at no additional charge for AWS Security Agent customers. During the preview, we welcome your feedback as we refine the experience. Use the built-in feedback mechanism in the Security Agent web application or reach out to your AWS account team.

Visit the AWS Security Agent console to enable full repository code review and run your first scan. For more information, see the AWS Security Agent documentation.

Cloud and AI are transforming industries and societies at unprecedented speed, from accelerating research and enhancing customer experiences to optimizing business processes and enriching public services. At Amazon Web Services (AWS), we believe that for the cloud and AI to reach their full potential, customers need control over their data and choices for how and where they run their workloads. In 2022, we formalized our commitment to control and choice—offering all AWS customers the most advanced set of sovereignty controls and features available in the cloud with the AWS Digital Sovereignty Pledge. As AI adoption accelerated, we’ve been working with customers to help them embrace AI innovation while meeting sovereignty requirements. We’re committed to ensuring customers can continue to harness AI’s transformative capabilities without compromising on the capabilities, performance, innovation, security, and scale of the AWS Cloud to meet their sovereignty needs, including AI sovereignty. Our approach to AI sovereignty is grounded in a deep understanding of these needs and the real-world implementation challenges that come with them.

Through discussions with customers, partners, analysts, and regulators, we’ve learned that digital sovereignty—and AI sovereignty—means different things to different stakeholders. Each country and region has unique, evolving sovereignty requirements, with no uniform guidance on which workloads or sectors must comply. Despite this variation, we’ve identified consistent themes: data sovereignty (including data residency and operator access restrictions) and operational sovereignty (including resilience, survivability, and independence). AI sovereignty builds on these foundations, adding emerging considerations such as preserving cultural norms, values, and local languages in AI outputs. Ultimately, meeting digital and AI sovereignty requirements comes down to providing customers with more control and choice.

AI sovereignty requires control and choice across the AI stack—comprehensive cloud infrastructure that combines compute, networking, data management, security controls, specialized application services, and talent. This includes the ability to make deliberate choices across the stack such as location, dependencies, services, and partners that align with customers’ unique needs, regulatory requirements, and innovation objectives. With AWS, customers can develop AI on a trusted foundation where their data remains secure and under their control. Customers have the freedom to choose from a comprehensive range of AI optimized chips—including purpose-built AWS silicon and chips from NVIDIA, AMD, and Intel—so they can select the right chip for the right workload. AWS applies two decades of learned expertise to our comprehensive AI stack, enabling organizations to maintain complete control over their data and operations while accessing cutting-edge capabilities to solve local challenges.

AWS provides customers with the infrastructure and tools to embed AI across the full value chain—not just in isolated use cases, but as a foundational capability enabling them to train and deploy models and build sophisticated AI and generative AI applications with exceptional performance. This enables customers to focus on innovation instead of their infrastructure, bringing the cloud to where they need it most with a range of options including AWS AI Factories, AWS Outposts, AWS Local Zones, AWS Dedicated Local Zones, and AWS Regions including the AWS European Sovereign Cloud. For example, customers who require dedicated deployments to meet their sovereignty requirements for their mission-critical AI workloads can use AWS AI Factories. These physically isolated, dedicated deployments built exclusively for the customer combine the latest AI infrastructure, including AWS Trainium accelerators, NVIDIA GPUs, dedicated networking, and storage. AWS AI Factories address AI sovereignty needs by delivering on-premises AI capabilities to securely perform training, fine tuning and real-time inference.

The AWS AI portfolio offers a comprehensive range of services—from foundation models (FMs) through Amazon Bedrock, to machine learning offerings like Amazon SageMaker, application services like Amazon Q, and developer tools like Kiro—designed to give customers control over their data and choice in how they deploy AI. With Amazon Bedrock, customers can choose from hundreds of models from leading providers like AI21 Labs, Anthropic, Amazon, Cohere, Mistral AI, and OpenAI. Customers can evaluate and select the most suitable FMs for their specific needs and choose where they deploy them, and fine-tune models privately with their own data. Customers are always in control of their data. Critically, no customer inputs to or outputs from Amazon Bedrock are used to train Amazon Nova or any third-party models.

Successful AI strategies require building a holistic environment nurturing local talent, supporting startups, developing industry-specific applications, and fostering public-private partnerships. The cloud has transformed AI from an exclusive technology requiring massive investment into an accessible tool for innovation across all sectors and organization sizes. While technical infrastructure gets much of the attention when considering AI sovereignty, the cultural and strategic dimensions of national FMs are equally critical. These FMs aren’t merely computational tools, they can encode elements of cultural knowledge, linguistic nuance, and societal context, making local relevance a design consideration rather than an afterthought. These FMs serve purposes that extend beyond technical capabilities. Locally trained FMs can reflect national educational curricula and cultural values while understanding local legal systems, business practices, and regulatory frameworks. Models trained on local languages, dialects, and cultural contexts support linguistic diversity and help underrepresented languages gain representation in AI products and services.

AWS supports vital national priorities and customers’ missions, such as the preservation of culture norms, values, and local languages development of regional and local language model capabilities. To customize models, customers can use Amazon SageMaker AI for voice, domain specialization, and to evaluate models for accuracy. For example, the first Greek LLM made available in March 2024 was Meltemi—built on top of Mistral-7B, running on AWS infrastructure, and continually pretrained to extend its proficiency in the Greek language using a dataset of 28.5 billion Greek tokens. Meltemi is available on HuggingFace. SEA-LION—a family of open source, multilingual LLMs for Southeast Asia—was trained entirely on AWS with managed GPU clusters. Their team completed a 3B-parameter model in only 3 months—a 60% faster timeline than comparable on-premises projects.

Sovereignty isn’t only about where data resides—it’s about who can access it and under what conditions. In the AI context, access restriction extends beyond infrastructure to cover model inputs, outputs, training processes, and the operational environments in which AI runs. Unlike traditional infrastructure, AI workloads introduce new access surfaces: the model itself, the data used to train it, and the inference pipeline through which sensitive inputs flow. This furthers the need for verifiable governance and identity propagation in IT systems.

To help ensure the confidentiality and integrity of customer data, all modern Amazon Elastic Compute Cloud (Amazon EC2) instances including those that offer AI accelerators, such as AWS Inferentia and AWS Trainium, are backed by the industry-leading security capabilities of the AWS Nitro System. By design, there is no mechanism for anyone at AWS to access customer data on Nitro EC2 instances that customers use to run their workloads. AWS services—including those with AI capabilities built on Amazon EC2—inherit these same protections. These protections apply to AI data running in the AWS Nitro System so that they’re protected at every stage—from model training to inference. The NCC Group, an independent cybersecurity firm, has validated the design of the Nitro System. We believe providing this level of transparency is critical in building and sustaining trust.

As AI agents increasingly take actions across systems on behalf of users, controlling who and what can access resources—and ensuring appropriate human oversight—becomes critical. AWS Identity and Access Management (IAM) helps ensure that only authorized users and applications can access AI resources through fine-grained permissions and comprehensive audit trails. For AI agents and automated workloads, Amazon Bedrock AgentCore Identity provides identity and credential management, so agents operate with the right permissions and nothing more.

Transparency is at the core of our digital sovereignty commitment. We provide comprehensive industry-leading technical measures, operational controls, and contract protections that give customers control over where they locate their data, who can access it, and how it’s used. To give greater assurance on how AWS services are designed and operated, we continue to seek out and secure third-party attestations, accreditations, and certifications that help our customers meet their compliance needs.

We continue to deepen our assurances and transparency to customers—such as updating our AWS Service Terms to reflect our technical protections commitments (e.g. AWS Nitro System), providing detailed commitments as to our handling of third-party requests for customer data in our agreements, and providing supplemental explanations and resources (e.g. CLOUD Act blog) to empower customers to make informed choices on sovereignty matters. These efforts extend into our commitment to responsible AI, providing customers the confidence to build and operate AI applications responsibly using AWS Services. ISO/IEC 42001 is an international management system standard that outlines requirements and controls for organizations to promote the responsible development and use of AI systems. AWS is the first major cloud service provider to achieve ISO/IEC 42001 accredited certification for AI services, covering Amazon Bedrock, Amazon Q Business, Amazon Textract, and Amazon Transcribe. In November 2025, AWS successfully completed its first surveillance audit for ISO 42001:2023 with no findings, reiterating the continual commitment of AWS to responsible AI practices.

Innovative technology requires a secure and trustworthy foundation. AWS supports more than 140 security standards and compliance certifications that our customers and partners can inherit to help comply with local laws and regulations. For two decades, we’ve deeply engaged with regulators and cybersecurity authorities to align our offerings with national priorities and ensure our solutions support both innovation and control. We actively contribute to frameworks that respond to new developments without stifling progress.

AWS is committed to giving customers the same control and choice over their AI systems as they have over their data. We help customers harness AI’s transformative power while maintaining the capabilities, performance, innovation, security, and scale of AWS Cloud. As cloud and AI evolve, AWS will continue offering the most advanced sovereignty controls and features available.

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If you’re looking to strengthen your organization’s security posture on Amazon Web Services (AWS) but aren’t sure where to start, then we’re here to help. Security Activation Days are complimentary, virtual, hands-on workshops designed to help you get practical experience with AWS security services in a single session.

Each Security Activation Day is a 3–6 hour virtual workshop where you work directly with AWS security services in real-world scenarios. Through a combination of presentations, demos, and workshops, you will get hands-on practice guided by AWS security specialists either in your own environment or in an AWS-provided sandbox.

Topics rotate across the full spectrum of AWS security, identity, and governance services, including threat detection and response, identity and access management, network and application protection, data protection, and governance and compliance. You will leave with actionable knowledge you can apply to your workloads immediately—not a to-do list of things to research later.

Security Activation Days are made for builders—security engineers, cloud architects, and DevOps teams who want to go deeper on specific AWS security capabilities. Whether you’re evaluating a service for the first time or looking to operationalize something you’ve already deployed, these sessions meet you where you are.

With over 6,400 attendees across 90 events so far in 2026, Security Activation Days consistently earn a 4.8 out of 5 satisfaction rating. Participants tell us the hands-on format is what makes the difference: there’s no substitute for actually configuring a service and seeing the results in real time.

We run Security Activation Days year-round across all time zones, with new sessions added regularly. Find a session, show up ready to learn, and start building today.

If you have feedback about this post, submit comments in the Comments section below.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

Amazon Web Services (AWS) achieved three Standar Nasional Indonesia (SNI) certifications for the AWS Asia Pacific (Jakarta) Region: SNI ISO/IEC 27017:2015, SNI ISO/IEC 27018:2019, and SNI ISO 9001:2015. SNI represents Indonesia’s national standards framework, comprising standards that are broadly applicable across industries within the country. These certifications further demonstrate that AWS services meet nationally recognized requirements.

The certifications were assessed by an independent third-party auditor accredited by the Komite Akreditasi Nasional (KAN), Indonesia’s National Accreditation Committee, in accordance with applicable local regulatory requirements, helping customers rely on trusted, locally recognized validation for their compliance needs.

All three certifications are based on international ISO standards adapted for Indonesia:

• SNI 27017 adds cloud-specific security controls that complement ISO/IEC 27001, helping you run workloads securely while reducing security assessment overhead.
• SNI 27018 focuses on protecting personally identifiable information (PII) in public clouds. This certification confirms that AWS handles your data according to international privacy standards.
• SNI 9001 establishes quality management systems that ensure consistent service delivery and continuous improvement across AWS operations.

Together with the existing SNI 27001 certification achieved in 2023, AWS is now the first cloud service provider (CSP) to hold all four SNI certifications—SNI 27001, SNI 27017, SNI 27018, and SNI 9001—demonstrating comprehensive alignment with Indonesia’s national standards for information security, cloud security, privacy, and quality management, and helping customers address a broad range of regulatory and risk management requirements.

Customers can access the corresponding certificates through AWS Artifact, a self-service portal that provides on-demand access to AWS compliance documentation. For a full list of AWS services covered under the SNI certification, see the Services in Scope compliance page

AWS continues to expand the scope of its compliance programs to help customers meet their architectural, business, and regulatory requirements. For more information regarding these certifications, contact your AWS Accounts team.

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 AI governance, risk management, and responsible AI practices. This guide helps cloud architects, AI/ML engineers, security teams, compliance leaders, and DevOps practitioners understand how to implement and operate ISO 42001-aligned controls using AWS services while applying the AWS Shared Responsibility Model for AI.

The guide explains how organizations can integrate AWS services into their AIMS to support the requirements defined in ISO 42001:2023 clauses 4–10 and the Annex A control specific to AI systems. It also highlights how AWS AI services, security capabilities, monitoring, and automation can help customers maintain visibility over AI systems, improve operational consistency, and prepare audit-ready evidence.

While AWS provides a secure and compliant cloud infrastructure with built-in responsible AI capabilities, customers remain responsible for defining their AIMS scope, implementing controls, and demonstrating conformity during certification audits.

Inside the guide:

• Overview of the ISO/IEC 42001:2023 framework, including understanding ISO 42001 and its Annexes, and how it relates to the broader ISO AI standards family
• Guidance for integrating with AWS security architecture and applying the AWS Shared Responsibility Model for AI workloads
• Context and scoping considerations for establishing an AIMS on AWS, including defining AI system boundaries within your environment
• Mapping of ISO 42001:2023 clauses 4–10 to AWS services and architectural capabilities, covering organizational context, leadership, planning, support, operation, performance evaluation, and improvement
• Implementation guidance for specific Annex A controls (A.2–A.10), including AI policies, internal organization, resources for AI systems, impact assessments, AI system life cycle management, data governance, transparency for interested parties, use of AI systems, and third-party and customer relationships
• Recommendations for evidence collection, documentation, and audit readiness using AWS native tooling
• Best practices for operationalizing AI compliance activities through automation and infrastructure-as-code

Use this guide to map ISO 42001 clauses and Annex A controls to your AWS environment, automate evidence collection, and reduce the effort involved in preparing for a certification audit.

Download: ISO/IEC 42001:2023 on AWS Compliance Guide

For further assistance, contact AWS Security Assurance Services

If you have feedback about this post, please submit comments in the Comments section below.

If you have feedback about this post, submit comments in the Comments section below.