Security Hub adds AI workload protection and multicloud support for Microsoft Azure

Security Hub is our foundation for full-stack enterprise security across clouds. It centralizes your security operations and turns raw signals into prioritized insights, so your team spends its time managing real risk instead of stitching tools together. Today that foundation grows in two directions our customers asked for most. We are adding purpose-built protection for AI workloads, and security monitoring for Microsoft Azure. Both are steps toward a bigger idea, that your best security tools should get smarter by working together.

These expansions came directly from customers, and they reflect where security is heading, not where it has been. The old promise of security tooling was a place to collect everything in one view. Collecting findings was never the hard part. The hard part is understanding them, connecting them, and acting before an attacker does, and doing it at the speed attacks now move. The programs that win from here will be the ones that see across their whole estate and respond fast, not the ones with the most dashboards. That is what we are building toward, and these launches are steps on that path.

Multicloud security management for Microsoft Azure

Customers across industries have made Security Hub a core part of how they run security on AWS. Most of them have run in more than one cloud for years, and they have been clear with us that they want Security Hub to also cover the rest of their estate. Today we do that for Microsoft Azure, with more clouds following quickly.

Security Hub now discovers Azure Virtual Machines, container images, Function Apps, and identities, then evaluates them for misconfigurations, internet exposure, and software vulnerabilities, with posture checks against the CIS Microsoft Azure Foundations Benchmark™. Azure findings are prioritized next to your AWS findings using the same finding format, automation, and response workflows, so your team works from one understanding of risk across your entire estate. Azure resources are priced at the same rates as equivalent AWS resources with no additional fees, and there’s an independent 30-day free trial. To learn more, see the What’s New post.

This is not actually our first move beyond AWS. Earlier this year we introduced Security Hub Extended, bringing best-in-class partner solutions across nine security categories into the same experience you already use. Those partner solutions protect endpoints, identities, email, browsers, and data wherever they run, across any cloud, on-premises, and everywhere your enterprise operates. Extended was already our first multicloud and multi-workload step. Today we broaden what our own native capabilities cover, and the two lines of work now advance together.

Protecting AI workloads

Every customer I talk to is building with AI. Generative AI on Amazon Bedrock, model training on SageMaker, agents orchestrating workflows through AgentCore. These workloads are reaching production faster than most security programs can keep up, and teams often don’t yet have the tools to monitor model invocations, track agent behavior, or even know what AI assets exist across the organization. One security leader told me his team only caught a compromised service account, one that had been invoking a foundation model thousands of times, because finance questioned the bill. They found a security incident through an accounting review. The visibility gap is real, and it is already expensive.

This summer we start closing it with three launches. Two are GuardDuty capabilities for threat detection and investigation, and a third is a new Security Hub AI inventory.

GuardDuty AI Protection (generally available)

Amazon GuardDuty AI Protection delivers threat detection purpose-built for Bedrock and SageMaker. It detects anomalous model invocations, cost harvesting attacks where adversaries abuse stolen credentials to run inference at your expense, and prompt injection attempts through integration with Bedrock Guardrails.

Cost harvesting is accelerating. When credentials are compromised, attackers increasingly use them to invoke foundation models. Inference is expensive, demand is high, and stolen access converts straight to value without deploying any infrastructure. GuardDuty analyzes CloudTrail data events, learns what normal invocation looks like at scale, and flags the deviations that signal compromise or abuse. This is detection that only works at AWS scale, because you have to see the signal across millions of workloads to know what normal is. GuardDuty AI Protection is now available to all GuardDuty customers with a 30-day free trial.

GuardDuty AI-powered investigations (preview)

AI-powered investigations take on the manual investigation work that drives alert fatigue and slows response. The capability automatically analyzes GuardDuty findings and the accounts around them to separate true threats from benign activity.

It examines finding context, related activity from the last 90 days, affected resources, and threat indicators, using knowledge graphs and threat intelligence to complete in minutes what used to take hours. Each investigation returns a disposition assessment with confidence scoring, MITRE ATT&CK® classification, supporting evidence, and clear recommendations to suppress, contain, or remediate. Your team focuses on genuine threats, whether across a single account or an entire AWS Organization, and mean time to resolution drops. GuardDuty AI-powered investigations is available in preview in 10 AWS Regions.

Security Hub AI inventory (generally available)

You can’t secure what you don’t know exists. Security Hub now provides an AI inventory, a continuously updated, organization-wide view of your AI assets and their security posture. As teams deploy models, agents, and pipelines, security often can’t see what’s running, and without connecting those assets to active threats and misconfigurations, it’s difficult to know what to secure first.

Security Hub AI inventory discovers and catalogs AI workloads across your AWS environment two ways. For managed services, it inventories AWS Config resources across Bedrock, SageMaker, and AgentCore. For self-hosted and external workloads, it finds models running on EC2, ECS, and EKS through runtime analysis, and identifies the external model endpoints your workloads make calls to. It maps each asset to the infrastructure beneath it, including compute, networking, IAM roles, and data stores, and correlates it with security signals such as GuardDuty findings. So when GuardDuty AI Protection flags an anomalous invocation, AI inventory immediately shows you which infrastructure is involved, what’s connected to it, and where it belongs in your priority order.

AI assets multiply fast. A developer spins up a Bedrock agent for a proof of concept. A data science team stands up a SageMaker endpoint for internal testing. Another team wires in an external model API through a Lambda function. Multiply that across hundreds or thousands of accounts and you can quickly lose track. AI inventory gives you that view across every account in your organization, available in your Security Hub Essentials plan at no additional cost.

A different approach to full-stack security

These launches share something worth pausing on. You didn’t procure AI protection as a separate product, and you won’t stand up separate operations for Azure. You add them to the Security Hub you already run, and they show up in your prioritized view of risk. That same idea is what Security Hub Extended extends to the rest of the security estate.

Security Hub Extended now has 21 curated partners across nine categories: 7AI, Britive, CrowdStrike, Idira (CyberArk), Cyera, Island, LayerX, Native Security, Noma, Okta, Oligo, Opti, Proofpoint, SailPoint, SentinelOne, Splunk, Sublime, Upwind, Varonis, Zenity, and Zscaler. These are best-in-class solutions across endpoint, identity, email, network, data, browser, cloud, AI, and security operations. None of them are here by default. Each one earned its place by committing to a shared view of where enterprise security is going, and by investing alongside us to build it. Curation is the point. A recommendation only means something if it can be turned down.

The commercial benefits of Extended are real today. Pay-as-you-go pricing, a single AWS bill, EDP eligibility, and no long-term commitments. But the work we’re most excited about goes further, and it’s not about procurement at all. Findings from every participating solution are emitted in the Open Cybersecurity Schema Framework (OCSF) and aggregated in Security Hub, and we’re building toward a single correlation across all of them, so a signal from an endpoint solution, an identity solution, and a cloud solution combine into one exposure and one attack path instead of three disconnected alerts. We’re working to reduce the deployment and onboarding effort between subscribing and seeing value. And we’re building the exchange that lets partner findings enrich each other, so the best-in-class tools you already trust become more than the sum of their parts. That is the differentiated future we’re investing in, and we’re building it in the open, guided by what customers ask for next. To learn more about Extended, see the What’s New post.

Accelerating forward

Step back and the shape of it is clear. Security Hub reaches across cloud providers, starting with Azure and expanding from there. It reaches across workload types with purpose-built AI protection and inventory. And it reaches across security categories through Extended and its curated partners. What began as a way to bring order to AWS security findings has become how more enterprises run full-stack security.

Detection and visibility are the foundation. What we build on top of them is a security experience that connects signals across every source you trust and helps you respond faster. It’s still Day 1, and Security Hub will keep extending as your environment, and the threats you face, continue to change.

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