What happened? 

The intrusion began with Storm-3068 gaining access to a user account through a self-service password reset process and then taking full control of the identity by registering its own authentication methods. With persistent access established, the threat actor shifted its focus to Azure DevOps using legitimate administrative tools and automated scripts to enumerate repositories, projects, pipelines, and deployment environments.

Azure DevOps proved to be a high-value target because it sat at the intersection of identity, software development, and cloud operations. By mapping trusted deployment paths and connected resources, the threat actor was able to identify opportunities to expand beyond the initial compromise.

The investigation revealed that Storm-3068 created a malicious pipeline designed to harvest Kubernetes credentials at scale. The pipeline deployed a kube agent and executed multiple jobs intended to collect kubeconfig files containing cluster connection details and authentication information. Leveraging the permissions of the compromised account, the threat actor deployed the pipeline that was authorized to access more than 50 resources and authenticated to services. In addition to deploying a kube agent, the threat actor modified pipeline scripts to install the Atera remote management agent and download the Chisel tunneling utility. These tools were deployed in an attempt to provide the threat actor with alternative mechanisms for remote access and to expose the Kubernetes API server. Chisel commands were executed to establish a reverse tunnel to an external IP address to enable potential remote interaction with the Kubernetes clusters.

Using Azure DevOps audit logs and Git version history, investigators reconstructed the next stage of the intrusion. The threat actor added seven stolen kubeconfig files to a repository, providing the credentials needed to access targeted Kubernetes clusters.

How did Microsoft respond? 

Once engaged, DART moved quickly to investigate the intrusion and disrupt the threat actor’s access. By analyzing telemetry across identity systems, development platforms, and cloud infrastructure, the team pieced together how the cyberattack unfolded and identified where the threat actor had expanded beyond the initial compromise.

Throughout the engagement, DART worked side by side with the customer, sharing findings through daily briefings and providing prioritized guidance to support containment and remediation efforts. As new details emerged, this close coordination helped the customer make informed decisions and respond quickly. DART also collaborated with Microsoft Threat Intelligence to place the activity in a broader threat context, helping refine the investigation and focus response efforts across affected environments.

Beyond containing the intrusion, DART provided recommendations to help improve resilience and reduce opportunities for future compromise. Read the full report to learn how the investigation uncovered the extent of the threat actor’s access and the key lessons organizations can apply to defend against similar identity-driven attacks. 

What can customers do to strengthen their defenses? 

 While the attack began with a compromised identity, its impact grew as the threat actor moved through development and cloud environments. Organizations can reduce similar risks by focusing on:

• Monitoring password reset activity for unusual patterns, including repeated reset attempts or activity targeting multiple users.
• Strengthening protection for privileged accounts by limiting exposure to self-service password reset workflows and requiring phishing-resistant multifactor authentication.
• Requiring approvals for code changes and enforcing branch protection policies to prevent unauthorized modifications.
• Restricting direct commits to critical branches so changes follow established review and approval processes.
• Controlling pipeline permissions and limiting who can create, modify, or execute build and deployment pipelines.
• Applying least-privilege access principles across identities, development platforms, and cloud resources to minimize the impact of a compromised account.

As this case demonstrates, a single compromised identity can become a pathway to much broader access when development platforms, deployment pipelines, and cloud infrastructure are tightly connected. Regular reviews of identity, DevOps, and cloud security controls can help reduce opportunities for threat actors to exploit those connections.

What is the Cyberattack Series? 

In our Cyberattack Series, customers discover how DART investigates unique and notable attacks. For each cyberattack story, we share: 

• How the cyberattack happened. 
• How the compromise was discovered. 
• Microsoft’s investigation and eviction of the threat actor. 
• Strategies to avoid similar cyberattacks. 

DART is made up of highly skilled investigators, researchers, engineers, and analysts who specialize in handling global security incidents. We’re here for customers with dedicated experts to work with you before, during, and after a cybersecurity incident.  

Learn more

To learn more about DART capabilities, please visit our website, or contact your Microsoft account manager or Premier Support contact. To learn more about the cybersecurity incidents described above, including more insights and information on how to protect your own organization, download the full report. 

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post ​​Beyond source code: A path to the keys to the kingdom appeared first on Microsoft Security Blog.

Microsoft introduces the cloud web applications threat matrix, a MITRE ATT&CK-aligned framework that helps defenders understand, prioritize, and mitigate threats to cloud-hosted web apps and serverless platforms.

Cloud-hosted web applications and serverless platforms create attack paths that can cross application code, managed runtimes, workload identities, deployment pipelines, and connected cloud resources. Investigating the application and underlying cloud platform separately can leave gaps in how defenders understand those paths.

Microsoft developed the Cloud web applications threat matrix to organize relevant techniques using MITRE ATT&CK tactics. The matrix can help security teams assess visibility gaps, prioritize hardening, and plan investigations across cloud-native environments. This blog introduces the framework, examines selected techniques, and outlines defensive priorities for reducing exposure.

Overview

Cloud-hosted web applications and serverless platforms let teams deploy and scale application logic quickly, but they also create attack paths that cross application code, managed runtimes, identities, deployment pipelines, and connected cloud services. These paths can be difficult to detect when the application layer and underlying cloud platform are investigated separately.

To provide a clear and consistent view of the threat landscape affecting cloud hosted web applications and serverless environments, we organize techniques using the MITRE ATT&CK format. Building on Microsoft’s previously published threat matrices for Kubernetes and storage services, this matrix expands coverage for cloud web applications– applications that execute code in a managed environment, are often tightly integrated with other cloud resources, and are commonly exposed to the internet.

The attack techniques presented in this matrix are divided into the following tactics, aligned with the MITRE ATT&CK framework:

• Resource Development

• Initial Access

• Execution

• Persistence

• Privilege Escalation

• Defense Evasion

• Credential Access

• Discovery

• Lateral Movement

• Collection

• Impact

Technique Catalog

Below, we walk through each tactic and describe its techniques in more detail.

Resource Development

The resource development tactic consists of techniques that adversaries use to establish resources they can use to support operations. This may include acquiring infrastructure, developing capabilities, or compromising resources that can later be used during targeting.

Subdomain takeover

Deleting a cloud application or service without removing its associated DNS record pointed to a reusable provider endpoint can create a subdomain takeover risk. Depending on the provider’s behavior, service configuration, and naming constraints, a threat actor may be able to register a resource that claims the same address and intercept traffic intended for the original service, potentially serving malicious content or harvesting credentials.

Initial Access

The initial access tactic consists of techniques that are used for gaining access to cloud web applications and serverless environments. This access can be achieved through compromised credentials, vulnerable applications, misconfigured interfaces, or by exploiting connected resources.

Application vulnerability

Running a public-facing web application that hosts a vulnerable application can enable adversaries to access and execute code in the context of the web application, or to access internal resources and gain a foothold in the cloud environment. Such vulnerabilities could stem from the application’s own code, its underlying framework, or third-party libraries and dependencies it uses.

Code injection in connected repository

Threat actors may inject malicious code into source repositories that are linked to cloud web applications or serverless functions. If these repositories are automatically synced with production environments, the injected code executes under the legitimate workflows.

For example, if a threat actor gains commit permissions to a GitHub repository that is configured to deploy GCP Cloud Functions through Cloud Build triggers, their code may be deployed into the application through the legitimate pipeline.

Compromised image in registry

Some cloud web applications are deployed from a container image pulled from private or public registries. Threat actors who get access to a private registry can plant their own compromised images or update an existing image with malicious code, which will run the next time the web application pulls the container image.

Exposed/misconfigured admin interfaces

Some cloud-based web applications expose administrative interfaces for managing deployments, configurations, or runtime operations. If these interfaces are exposed to the internet or misconfigured, threat actors might be able to access them and view critical data, execute commands, or manipulate application behavior.

For example, if an Azure App Service exposes its Kudu interface to the internet, a threat actor with sufficient credentials could execute commands in the app’s environment.

Serverless trigger injection

In cases where the application executes backend workflows in response to event-driven triggers, an end user who can directly or indirectly influence those triggers may cause unintended activity within the application. By manipulating inputs such as crafted file uploads, queue messages, API calls, or other event sources, a threat actor can force serverless functions to run with their supplied data, which could lead to unintended code execution, data access, or further compromise.

For example, a threat actor might upload a modified image file containing a crafted payload through a legitimate web form. The image is then stored in an S3 bucket, which triggers an AWS Lambda function configured to process new uploads. If the function handles the file without proper validation, the threat actors payload could cause unintended behavior or even lead to remote code execution.

Using deployment credentials

In some cloud web applications, deployment credentials can grant management access beyond publishing new code. Adversaries who obtain such credentials might be able to use them to directly interact with the application without modifying its source code.

Azure App Service, compromised deployment credentials can allow access to deployment and SCM (Source code management) interfaces, which may enable file access, command execution, or application modification depending on the app configuration and credential scope.

Execution

The execution tactic consists of techniques that are used by threat actors to run their code inside cloud web applications and serverless environments.

Application exploit (remote code execution)

Deployed web applications that contain a remote code execution vulnerability, or a vulnerability that could eventually lead to code execution, can enable threat actors to run malicious code in the web application context. If the application has access to any additional resources, then the threat actor could access those as well.

Cloud native terminal

Some cloud platforms provide built-in administrative consoles or SSH-style terminals for running commands directly inside the application’s execution environment. Threat actors who gain access to the terminal may be able to extract data, edit the web app files and execute commands.

For example, Azure App Services expose a Kudu console that acts as a built-in terminal; if threat actors obtain deployment credentials, they can use it to browse files, execute commands, and tamper with application code.

Site extensions

Site extensions are an Azure App Services feature that allows users to install additional tools and utilities onto their web application. These extensions run within the context of the App Service and have the same permissions as the application itself – including requests data, file system access and environment variables. Site extensions are installed from a NuGet-based feed that allows third-party package submissions. If threat actors publish a malicious extension that resembles a legitimate package, or compromise an existing package, users who mistakes the package for a trusted extension may install it, allowing the threat actors code to run in the application context.

Persistence

The persistence tactic consists of techniques that are used by threat actors to maintain access to cloud web applications in case their initial foothold is lost.

Cron jobs

In cases where a cloud application uses scheduled or trigger-based tasks, a threat actor with the ability to create or modify such jobs can cause their malicious code to execute automatically. Because these jobs can run independently of normal request flows and often inherit the application’s privileges, control over a scheduled or event-triggered job allows persistent execution even if the main application code is updated.

For example, if a threat actor is able to create or modify a WebJob in Azure App Service, their code will periodically run on the web application, regardless of changes or updates to the application code itself.

Source code modification

A threat actor with access to a development environment may be able to modify the application’s source – which could reside in a git repository, a container image in a registry, or a deployment package in cloud storage. Because cloud web applications are typically deployed through automated pipelines, a single modification can propagate automatically into production, causing the threat actors code to run every time the application restarts. These changes become part of the application’s canonical source, meaning that even if the runtime environment is rebuilt or scaled, the tainted code is redeployed from the same trusted source, maintaining the threat actor access to the application.

Valid cloud accounts

Adversaries may gain access to cloud web applications and serverless environments by leveraging compromised valid cloud accounts. Using legitimate credentials allows threat actors to interact with such services without raising suspicion. This enables them to deploy or modify application code, configure triggers, and maintain control over workloads.

For example, a threat actor who compromises an Entra ID user with sufficient owner-level permissions on a subscription may be able to read or modify function app resources within that scope, subject to resource and policy controls.

Privilege Escalation

The privilege escalation tactic consists of techniques that are used by threat actors to get higher privileges in the environment than those they currently have. This can include accessing workload identity credentials or leveraging application permissions to access additional cloud resources.

Access cloud resources

Web apps deployed in the cloud often run with identities or service accounts that have permissions over additional cloud resources in the environment such as storage, databases and AI services. Additionally, some applications store connection strings or keys to cloud resources in the app configuration files or environment variables. Therefore, if threat actors compromise the application, they can often extract or leverage these credentials to access additional cloud resources.

Access workload identity credentials

Workload identities are identities that are managed by the cloud provider and can be allocated to cloud resources. The identity’s secret is fully managed by the cloud provider, which eliminates the need to manage the credentials. Web apps can use workload identities to perform actions on other cloud resources by querying Instance Metadata Service (IMDS) or similar endpoints. Threat actors who gain access to a web app can leverage their access to the IMDS endpoint to get the workload identity’s token. With a token, the threat actors can access cloud resources.

For example, in Azure App Services, the managed identity access token can be acquired through a local identity endpoint, which is defined in the environment variables (IDENTITY_ENDPOINT). If a threat actor is able to execute code on such an App Service instance, they would be able to query the endpoint and receive an access token to other Azure resources with the managed identity permissions.

Defense Evasion

The defense evasion tactic consists of techniques that are used by threat actors to avoid detection and hide their activity.

Development slots

Many cloud platforms and serverless environments support staging or preview environments (such as deployment slots in Azure App Services, aliases in AWS Lambda, or revision tags in GCP Cloud Run), which allow developers to test and stage new versions of their applications before swapping them into production. These environments can be swapped or promoted with minimal downtime. If a threat actor gains the ability to modify or promote a non-production environment, they may execute malicious code or gain insights into the application’s structure and behavior. In some cases, these staged environments are directly accessible without a swap, meaning a threat actor could execute code in a staging slot or alternate version and potentially evade detection, since the primary production deployment remains untouched.

For example, in Azure App Service, a threat actor who obtains permissions to manage a staging deployment slot could either swap it into production, thus pushing malicious code live, or exploit the slot’s separate URL to run the malicious app without modifying the production’s code.

Disable cloud logging

Threat actors with appropriate permissions may disable or alter cloud logging to hide their actions and avoid detection. This can include turning off diagnostic logging on a web application, deleting or modifying existing log data, changing log retention policies to accelerate log expiration, or redirecting log output. By suppressing logging, the threat actor reduces the visibility that defenders have into ongoing malicious activity, making it harder to detect the compromise, perform incident response, or reconstruct the attack timeline.

Credential Access

The credential access tactic consists of techniques that are used by threat actors to steal credentials. In cloud web application environments, this includes credentials of the running application, workload identities, secrets stored in configuration, or cloud credentials.

Brute force

Some web applications or interfaces may still use basic authentication, either for user access, administrative functions, or deployment interfaces. A threat actor could try to gain access by repeatedly attempting credential combinations, and upon finding valid credentials, use them to access and use the relevant privileges.

For example, Azure App Service exposes the Kudu management console (the SCM site) and FTP endpoints that support basic authentication. This includes user‑scoped deployment credentials, which are manually set by the user and shared across all App Services within a subscription that the user has access to. If a threat actor is able to successfully guess those credentials, they could gain deployment access to multiple applications in the subscription.

Cloud credentials in runtime environment

Some web applications store secrets such as keys, tokens, and connection strings in environment variables or configuration files. In cloud environments, those secrets are often used to access additional cloud services within the environment. If a threat actor gains access, even read-only, to the running application environment, they would be able to retrieve those credentials and use them to authenticate against those external cloud resources.

For example, an Azure Function configured to authenticate to Azure OpenAI with a resource key may store that key and the service endpoint in application settings exposed as environment variables. a threat actor who accesses those variables could use the key to make authorized data-plane API requests to the associated Azure OpenAI resource.

Discovery

The discovery tactic consists of techniques that are used by threat actors to explore the environment to which they gained access. This exploration helps the threat actors to perform lateral movement and gain access to additional resources.

Access to connected cloud storage

Cloud applications often use external storage services for hosting source code, configuration files or assets. Threat actors may exploit misconfigured or compromised read access to this storage to review the code and configuration to find vulnerabilities or sensitive information that could be exploited to take over the application.

For example, in GCP Cloud Run functions, the function code is saved into a bucket in the project. If a threat actor compromised a user with storage read access, they would be able to view the source code.

Cloud service discovery

Cloud‑hosted applications often contain configuration values or runtime information that reference other cloud services the application interacts with, such as service URLs, API endpoints, database connection strings, or resource identifiers. After gaining access to a web application, threat actors can discover additional cloud resources through environment variables, network connections or application code.

Instance metadata API

Cloud platforms expose metadata services that provide information about the running environment, such as instance details, network configuration, and identity credentials. In some cases, this service is available from within cloud web applications as well. Threat actors who gain access to such an application may query the metadata API service to get information about the underlying VM and the application environment.

Lateral Movement

The lateral movement tactic consists of techniques that are used by threat actors to move through the victim’s environment. In cloud web application environments, this includes gaining access to connected cloud resources, third-party services, or internal network resources.

Connector reuse

Cloud applications may use managed connectors or integration resources to interact with third-party services such as email providers, SaaS platforms, databases, or messaging systems. These connectors sometimes store authentication or authorization details – such as OAuth tokens and access keys, that are separate from the web application’s own identity and thus could be reused across multiple applications. A threat actor who compromises a user or identity with permissions over the connector resource can invoke those stored credentials to access the connected third-party services, enabling lateral movement beyond the cloud environment.

For example, in Azure Logic Apps, API connections are standalone resources that store authenticated sessions to external services, such as Office 365, Slack, or SQL databases. A threat actor with sufficient permissions on the resource group can create a new app that uses existing API connectors, triggering actions on the connected services using the stored credentials without needing to extract the underlying secrets.

Collection

The collection tactic consists of techniques that are used by threat actors to collect data from cloud web applications or connected resources.

Access application database

Many applications rely on a connected database to store application data, user information, configuration values, or state. The application often connects to the database by using the application’s cloud identity, or by using a hardcoded connection string. If a threat actor gains code execution abilities, they can interact with the database – query and extract data or modify entries. In cases where the database is accessible from the internet, threat actors may only need read permissions over the web app to access the database.

Event data capture

Cloud applications often generate logs that include diagnostic data, request metadata, or user input. Due to misconfigured logging levels or insufficient filtering, these logs may inadvertently contain sensitive information such as credentials, personally identifiable information (PII), or details about the application environment, including internal paths, dependency versions, and cloud resource names. This information could assist adversaries in furthering their attacks. Logs may be stored locally, streamed to external services, or accessed through debugging interfaces. Logs may be stored locally, streamed to external services, or accessed via debugging interfaces. If a threat actor gains access to the application or its logging infrastructure, they can collect this data to aid further exploitation or reconnaissance.

For example, AWS Lambda functions automatically send all standard output to CloudWatch Logs. If verbose or debug-level logging is misconfigured and left enabled in production, sensitive data may end up in the log group. A threat actor who gains read access to CloudWatch can then harvest this information.

Impact

The impact tactic consists of techniques that are used by threat actors to destroy, abuse, or disrupt the normal behavior of cloud web applications and their environments.

Data destruction

Threat actors who gain sufficient privileges within a cloud web application may delete or corrupt data stored in the app or in connected cloud resources such as databases and storage.

Data theft

If threat actors gain access to the application, its storage, or connected cloud resources, they may be able to retrieve data stored or processed by the application. This includes application content, user information, configuration files, or proprietary content.

Defacement

Adversaries may attempt to alter the web application’s content or appearance to damage reputation, intimidate victims or spread propaganda. This could be done through access to the application itself, to the source code or any assets it uses.

Denial of wallet

Cloud applications often scale dynamically based on demand, incurring costs for compute, storage, and data transfer. Threat actors may intentionally trigger operations that will cause those resources to scale out to impose financial damage. One such approach is to flood a web application with requests, similar to traditional denial-of-service (DoS) attacks. This will cause the application to allocate more resources, thus causing increased charges.

For example, a threat actor could repeatedly invoke a Cloud Function with high memory allocation, leading to inflated billing due to excessive execution time.

Resource hijacking

Threat actors may leverage the compute, network, or storage resources of the application for unauthorized purposes, such as cryptocurrency mining, mass scanning, or traffic proxying.

Mitigation and protection guidance

As organizations adopt cloud-native and serverless architectures, defending against these threats requires visibility across both application behavior and underlying cloud resources. The cloud web applications threat matrix is intended to support this by mapping techniques to attack stages, helping defenders identify where visibility exists and where gaps remain.

Mitigation strategies for individual techniques are detailed within the matrix. Across the matrix, recurring priorities include requiring multifactor authentication, applying least-privilege permissions to users and workloads, and restricting access to applications, deployment environments, and connected resources.

Organizations should also protect source repositories, build systems, and deployment pipelines from unauthorized changes, and install packages and extensions only from trusted sources. Reusable credentials should not be stored in source code or configuration files. Workload identities and secrets management solutions should be used where supported, while network access to sensitive services should be limited to authorized networks.

To support investigation, organizations should centralize security-relevant logs in protected locations and prevent unauthorized changes to logging configurations. Resource quotas, concurrency limits, cost guardrails, and spending alerts can help reduce the impact of resource hijacking and denial-of-wallet activity. Organizations should also maintain and test backup and recovery plans to prepare for destructive operations.

Microsoft Defender for Cloud and Microsoft Defender XDR can support investigation and response across many related signals, including cloud resource posture, workload activity, identity activity, and cross-domain incidents, depending on customer configuration and available telemetry.

References

• Threat Matrix for Cloud Web Applications

• MITRE ATT&CK®

• Threat Matrix for Kubernetes

• Threat Matrix for Storage Services

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

Review our documentation to learn more about our real-time protection capabilities and see how to enable them within your organization.  

• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Microsoft 365 Copilot AI security documentation
• How Microsoft discovers and mitigates evolving attacks against AI guardrails
• Learn more about securing Copilot Studio agents with Microsoft Defender 

The post Threat matrix: Mapping threats across cloud web applications appeared first on Microsoft Security Blog.

At Microsoft we encompass these security requirements, along with threat knowledge and operational frameworks in our Secure Future Initiative (SFI), to guide what a well-defended cloud service looks like. But defining the requirements is only the start. Meeting them means continuously evaluating our live services against them, at AI speed.

That is why Microsoft built a multi-agent AI system that proactively evaluates and hardens our cloud infrastructure—matching the speed, scale, depth, and quality needed for our unique hyper-scale production environments. This system is purpose-built to evaluate Microsoft’s own cloud services against our stringent security requirements and make our infrastructure harder to compromise. While this is an internal capability and not available as a customer-facing product or service, the insights and patterns we develop through this work will inform how we improve our products over time. This system complements existing tools in Microsoft’s security ecosystem. For example, this system incorporates code-level vulnerabilities, including from systems like codename MDASH and adds configuration, identity, network, and runtime context, to assess overall service security posture.

A modern AI architecture for proactive defense

Vulnerabilities don’t just live in code. They emerge from the interplay between how a service is built, configured, deployed, and connected. Consider a cloud service where the application code passes every security review, the identity configuration follows least-privilege policy, and the network rules restrict inbound traffic as designed. Individually, each component is compliant. The system evaluates the service as a whole and may find that a combination of a permissive service-to-service trust relationship, a token scope that grants broader access than the service requires, and a deployment configuration that exposes an internal API to an adjacent network tier creates a composite vulnerability that no single-component review would surface.

At its core, the system employs a multi-tier agent hierarchy: orchestration agents for workflow management, analysis agents that specialize in security reasoning and are grounded in Microsoft’s threat intelligence—including emerging patterns and threat actor activity—and evidence-gathering agents that investigate across code repositories, infrastructure definitions, identity configurations, runtime settings, network topologies, and live resource states.

The result of this multi-stage analysis is a comprehensive security understanding of each service that goes beyond what any single analysis method can provide on its own. Compared to traditional human-led security reviews that take weeks, the system compresses the same depth of analysis into hours.

How it works: The system follows a multi-stage analysis pipeline, where each stage builds on the one before it:

1. Profiles each service architecture to understand components, data flows, trust boundaries, risk exposure, and more.
2. Enumerates applicable security controls based on SFI requirements across identity, network, tenant isolation, engineering systems, and detection domains.
3. Verifies control implementations against real-world code, configurations, and cloud resources.
4. Evaluates defense-in-depth coverage to help ensure layered protections exist across all control domains.
5. Identifies where controls are missing, misconfigured, or brittle, and maps the compensating controls that determine whether a gap is exploitable in practice.
6. Produces compensating controls and durable fix recommendations for immediate-risk reduction while driving lasting remediation.
7. Continuously learns and improves by incorporating feedback from security reviewers and service teams, and by tapping into Microsoft’s evolving threat intelligence to adapt to new patterns.

Core design principles

The analysis pipeline is shaped by four principles that determine how the system reasons about security:

1. Frontier-ready architecture

The system is built with modular model interfaces that can take advantage of new frontier capabilities as they emerge. New models, enhanced planning, and execution capabilities can be integrated behind stable agent interfaces—preserving existing tooling, orchestration, knowledge, pipelines, reporting, and governance.

2. Compositional risk reasoning

The system uses “what-if” agentic ideation to reason compositionally about risk. It explicitly explores how individual security gaps can chain together into multi-step attack paths. For example, a minor misconfiguration in identity, combined with a seemingly unrelated network exposure, and a missing data encryption control, might together enable a serious breach. Modern attacks are often complex sequences rather than single bugs, and the system is designed to help identify and analyze them. By running diverse models and large-scale reasoning trials in parallel, the system explores an expansive space of scenarios that traditional static analysis or single-scan tools would miss.

3. Service-specific adaptation

Cloud services aren’t one-size-fits-all, so security analysis shouldn’t be either. Rather than applying a fixed checklist, the system builds a service-specific understanding of each service it analyzes. It profiles the service in depth—identifying its components, mapping data flows, locating trust boundaries, and determining which security controls should apply given that service’s unique architecture and risk profile. If a service uses a novel pattern, a microservices architecture spanning multiple codebases, or an agent-to-agent communication model, the system adapts its analysis to account for those patterns. This adaptive approach, guided by current SFI requirements, means that the system can tackle emerging cloud paradigms that don’t fit traditional security checklists.

4. Defense-in-depth evaluation

A key focus area for SFI is layered defense. The system asks two questions: “What vulnerabilities exist?” and “Where does this service lack multiple lines of defense?”. It evaluates whether critical security domains have overlapping, robust controls, and it flags any missing or brittle layers—even if no immediate exploit is identified.

For example, the system will highlight a scenario where a service might have a weak network segmentation or an overly permissive admin role—even in the absence of a known attack—because those gaps mean a single failure could lead to a compromise.

This forward-looking, “assume breach” analysis embodies the Zero Trust and defense-in-depth principles reinforced by SFI. In an era when AI-assisted attackers can enumerate systems faster and chain together weaknesses more systematically, ensuring redundant safeguards is increasingly critical.

The assurance tree: SFI in action

At the core of the system are the SFI engineering and security principles: a structured body of security requirements shaped by years of hardening the Microsoft infrastructure. These requirements guide what the system evaluates, how it reasons about risk, and the recommendations generated. When security expectations evolve—whether to address a new class of threats or incorporate lessons from remediation—the system’s reasoning evolves with them. The assurance tree is how we express these requirements: a structured, hierarchical map of security controls that the system expects a service to have in place, tailored to that service’s usage and design.

As the system profiles a cloud service, it generates an assurance tree tailored to that service. At the top level of the tree are the fundamental security domains, that map to the SFI pillars. Each of these domains is recursively decomposed into more granular controls and sub-controls tailored to the service. For instance, Identity security decomposes into controls for password policies, OAuth token handling, and MFA enforcement—down to verifying that the service’s code correctly validates a JSON Web Token’s issuer and expiration. The assurance tree guides the system’s evidence-gathering agents to verify that thousands of expected controls are in place and effective—or to identify where something is missing.

This approach turns security from an open-ended hunt into a systematic verification of the SFI requirements: the system is essentially asking, “Have all the security measures that should protect this service been properly implemented?”. Crucially, it goes further—considering how individual gaps might combine, helping to ensure that even combinations of missing controls are identified and addressed.

Proven results: From theory to practice

Within a few months, the system has enabled Microsoft security engineering teams to proactively harden our cloud services. It generates findings and recommendations which our security engineering teams then validate and implement. Because the system evaluates the whole service in context and reasons about the severity and exploitability of each issue before surfacing it, its findings have proven high quality and actionable: more than 90% have been confirmed as genuine security issues by our security engineers, enabling proactive action to improve security posture. Just as important as the volume and precision of findings is their nature. Many issues the system discovers are nuanced, cross-domain vulnerabilities that wouldn’t have been caught by traditional methods. For example, the system has uncovered security gaps that only become apparent when considering code, configuration, and cloud resources together—the kind of issue that isolated scans or compliance checklists could overlook.

This capability allows us to enhance how we do security reviews. Traditionally, a deep security review of a complex service might span weeks of effort by multiple domain experts. The system can achieve a thorough review in a matter of hours—allowing teams to assess more services, more frequently.

The path forward: Applying these principles in your environment

If you are responsible for security at your organization, the key question is whether your defenses are keeping pace. AI models will continue to evolve. The organizations that are hardest to compromise will be the ones that have layered, verified controls already in place—not the ones that react fastest after something is found.

Based on what we have learned from building and operating this system, here are three principles any organization can apply now:

1. Go beyond code scanning to system-level discovery. The most consequential issues emerge not from a single bug, but from how factors including code, configuration, identity, and network interact in production. Collect rich signals across these domains and evaluate your services as composed systems, not isolated components. Prioritize composite attack paths over individual findings.
2. Move beyond known vulnerability patterns to proactive defensive controls. Traditional scanning asks, “Is there a known bug here?” Proactive hardening asks, “Does this service have comprehensive controls and layered defenses?” Reason about not just vulnerabilities, but controls, and how defense-in-depth coverage can improve protection before a specific exploit is discovered.
3. Integrate AI to drive proactive prevention at machine speed. The same AI capabilities that accelerate vulnerability discovery can be applied to continuously evaluate whether security controls are correctly implemented, layered effectively, and working as intended. Organizations that adopt AI-powered proactive evaluation will identify and close gaps faster than those relying solely on periodic manual review.

For deeper guidance on implementing AI-powered defense for an AI-accelerated threat landscape, customers can review Secure Now guidance for AI‑powered security and proactive defense. Any customer with a Microsoft Entra ID can access it. Microsoft Security customers will also have access to capabilities that enable them to assess their exposure and take action.

Moving forward, we will share more about how we are scaling our response operations to match machine speed and how SFI’s engineering practices are evolving for this new reality.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post Protecting Microsoft at AI speed: How SFI proactively hardens our cloud   appeared first on Microsoft Security Blog.

Frost & Sullivan’s 2025 Frost Radar™ for Cloud Security Posture Management points to a structural shift: CSPM is no longer a periodic compliance exercise. It’s a continuous, risk‑based governance layer inside modern cloud native application protection platforms (CNAPPs). Frost & Sullivan projects the CSPM market will grow from $2.82 billion in 2025 to $6.96 billion by 2030 at a 19.8% compound annual growth rate (CAGR)—reflecting the growing shift from standalone posture tools to integrated, platform‑based approaches.

A cloud native application protection platform (CNAPP) brings together posture, workload protection, identity and entitlement management, and related controls to secure applications across the full lifecycle—from development through runtime operations.

Frost & Sullivan’s analysis also reinforces Microsoft’s position among leading CSPM providers, with strong performance across innovation and growth. This reflects Microsoft’s approach to unifying posture management with workload protection, identity, and data security as part of a broader CNAPP platform—aligning directly with how CSPM is evolving from point-in-time compliance to continuous risk management.

Below are five key insights from the Frost Radar and what they mean for security leaders navigating today’s cloud threat landscape.

1. CSPM is becoming the governance layer for CNAPP 

Frost & Sullivan research suggests CSPM is evolving beyond a standalone tool focused on configuration hygiene. Instead, it increasingly serves as the entry point and governance backbone for CNAPP—integrating posture signals with workload protection, identity, data security, and security operations center (SOC) workflows.

Modern CSPM solutions are expected to:

• Provide continuous visibility across infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS).
• Correlate misconfigurations, identities, vulnerabilities, and data exposure.
• Feed high‑fidelity posture context into runtime protection and incident response workflows.

What to look for

Unified visibility that connects posture findings with workload, identity, and data signals—so investigations don’t begin from scratch when posture risk turns into an incident.

Frost notes that by 2030, CSPM is expected to become less a standalone market and more a foundational governance layer inside CNAPP platforms—unifying code‑to‑cloud policy and feeding posture context into runtime and SOC workflows

2. The market is moving beyond compliance to risk‑based prioritization

Compliance coverage is now table stakes. Frost highlights that for organizations to differentiate they need solutions that continuously assess risk, reduce noise, and guide remediation—helping teams focus on the “toxic combinations” that create real exposure.

Leading solutions need to:

• Continuously assess risk rather than rely on point‑in‑time scans.
• Reduce alert fatigue through contextual correlation.
• Prioritize remediation based on exploitability and business impact.

Organizations are increasingly using CSPM to drive ongoing risk reduction—with compliance reporting treated as an outcome of stronger controls.

What to look for

Prioritization that highlights likely cyberattack paths—not just severity scores—so teams can fix what’s exploitable first and minimize false positives.

Security leaders are adjusting how they evaluate CSPM vendors in response to these shifts. Rather than asking how many compliance frameworks a solution supports, they’re looking at whether posture insights can be correlated with identity, workload, and runtime signals to expose exploitable attack paths and guide remediation across developer and SOC workflows. Frost & Sullivan’s evaluation framework reflects this transition—placing greater emphasis on integrated, code to cloud risk management capabilities inside broader CNAPP platforms.

3. Code‑to‑cloud visibility is now required

Another major theme in the Frost Radar report is how organizations can embed posture management earlier in the application lifecycle to prevent misconfigurations before deployment—and continuously detect drift as environments change.

The report emphasizes:

• Infrastructure‑as‑code (IaC) scanning and policy‑as‑code enforcement
• Continuous integration and continuous delivery (CI/CD) pipeline integration
• Ownership mapping so issues are routed to the right developer or team

By extending posture management into DevSecOps workflows, organizations can reduce remediation costs and prevent risk from reaching production.

What to look for

Security guardrails embedded in CI/CD pipelines—with clear ownership routing—so remediation happens earlier and doesn’t bounce between teams.

4. Multicloud complexity is driving platform consolidation

Fragmented tools and siloed data continue to create blind spots across posture, identity, and workload risk—overwhelming SOC teams and reducing operational effectiveness.

As a result, buyers are consolidating point products into integrated CNAPP platforms that correlate posture, workload, identity, and runtime signals.

Platform convergence is reshaping CSPM investment and deployment models:

• A growing share of CSPM capability is delivered as part of a broader platform.
• Shared dashboards improve visibility across hybrid and multicloud environments.

Consolidation reduces tool sprawl and improves SecOps efficiency.

What to look for

A platform approach that standardizes policies across clouds and carries posture insights into security operations (SecOps) workflows—improving both signal quality and remediation speed.

5. AI is reshaping CSPM—from operations to new workloads

Frost highlights AI as both an operational enabler and a new security domain for CSPM.

AI is being used to:

• Reduce alert fatigue through contextual prioritization.
• Generate compliance evidence.
• Deliver guided remediation for developers and security teams.

At the same time, CSPM capabilities are expanding into AI workload posture management—covering models, pipelines, and related infrastructure.

What to look for

AI assisted prioritization and guided remediation—plus posture coverage for AI workloads—so emerging risks such as prompt injection or data leakage are managed alongside traditional cloud risk.

What this means for security leaders

Frost & Sullivan’s analysis underscores that CSPM is no longer about checking compliance boxes—it’s becoming a strategic control layer for managing cloud risk across the entire application lifecycle.

If you’re evaluating CSPM capabilities in 2025–2026, ask:

• Can posture findings be correlated with identity, workload, and data context to expose exploitable cyberattack paths?
• Can security guardrails be embedded earlier in CI/CD pipelines through IaC and policy‑as‑code?
• Can posture insights flow into SOC workflows for faster investigation and response?
• Can risk be continuously prioritized across multicloud environments—not just reported periodically?

How Microsoft aligns with CSPM’s next phase

Frost & Sullivan attributes Microsoft’s leadership in CSPM to its ability to operationalize posture management as part of a broader cloud security platform—aligning with the report’s emphasis on integrating posture with runtime protection, identity, data security, and SecOps workflows across the application lifecycle. These capabilities align with the same governance, prioritization, DevSecOps integration, and lifecycle visibility themes highlighted across the Frost Radar insights above.

Rather than operating as a standalone compliance layer, Microsoft correlates posture data with runtime telemetry and identity signals—integrating findings into developer pipelines and SOC workflows through GitHub, Azure DevOps, and Microsoft Defender XDR. Frost highlights Microsoft’s multicloud visibility across Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP); policy‑as‑code enforcement and CI/CD integration to strengthen shift‑left security; and unified dashboards that carry posture context into investigations and response.

The Frost report also notes Microsoft’s expansion into emerging posture domains—including AI and API posture management—to continuously manage cloud and AI workload risk across the application lifecycle.

Learn more

• Read the Frost & Sullivan Frost Radar™ for Cloud Security Posture Management (2025) to see how CSPM leaders are evaluated—and what capabilities matter most as vendor selection criteria shift toward integrated CNAPP platforms.

• Explore Microsoft cloud security solutions to see how unified posture management, risk prioritization, and protection across the application lifecycle can help reduce cloud risk.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post 5 insights from Frost & Sullivan’s 2025 Frost Radar™ for Cloud Security Posture Management appeared first on Microsoft Security Blog.

As organizations expand across multicloud and hybrid environments, they adopt modern architectures built on containers, Kubernetes, microservices, APIs, and AI-powered workloads. This increases both the volume and interconnectedness of security signals. The challenge is no longer identifying individual risks, but determining how vulnerabilities, identities, and data exposures combine across infrastructure and the applications running on it to create real attack paths, and which of these are most critical to fix at the source. Effective risk reduction depends on understanding which of these paths are actually reachable and exploitable in a live environment.

Frost & Sullivan’s 2026 Frost Radar™ for Cloud/Application Runtime Security (CARS) reflects this shift. The report highlights how cloud security is evolving from a collection of posture and workload capabilities into a unified runtime risk operations model, correlating signals across code, cloud, runtime, applications, and security operations center (SOC) workflows to prioritize and reduce risk continuously.

Within this evolving market, Microsoft is positioned as a visionary leader because of the scale of its hyperscale ecosystem, operational breadth of Microsoft Defender for Cloud when integrated with Microsoft Defender XDR, and large customer base. That recognition reflects where the category is heading: toward platforms that connect cloud and application security into one operational view of risk.

Why cloud security is being redefined

The Frost Radar makes a clear point: cloud security is no longer about visibility or compliance alone. It is becoming an operational discipline for reducing risk across the full runtime—from cloud infrastructure to the application code executing on top of it.

Modern environments introduce complexity across:

• Multicloud and hybrid infrastructure.
• Rapid development and continuous deployment.
• Containers, serverless, microservices, and APIs.
• AI-powered workloads, agents, and machine identities.

This complexity exposes the limits of traditional, siloed tools—where cloud posture, workload protection, and application security each live in their own console. Organizations now need platforms that can:

• Correlate posture, runtime, identity, data, and application signals.
• Prioritize risk based on exploitability—not severity alone.
• Integrate security across development, cloud operations, and the SOC.
• Validate whether a vulnerability is actually reachable inside a running application.

This is the shift the report describes: from detecting issues to operationalizing risk reduction across the lifecycle—and across both cloud and application layers.

What distinguishes leading platforms

Frost & Sullivan evaluates providers on growth and innovation—but, more importantly, on how effectively they help organizations manage real risk. Five themes define the next generation of platforms:

1. Platform unification over point solutions.
2. Code-to-cloud-to-SOC integration.
3. Risk prioritization based on exploitability.
4. Correlation across identity, data, cloud, and application context.
5. Expansion into AI-powered workloads.

Taken together, these capabilities represent a move from fragmented visibility to connected, contextual risk management that spans cloud detection and response (CDR) and application detection and response (ADR)—the two halves the market is converging into a single runtime fabric.

How Microsoft help organizations manage real risk

1. Connect signals to prioritize real attack paths

Most security tools surface large volumes of findings across cloud infrastructure and applications, but isolated findings do not reflect how cyberattacks actually happen. Threat actors exploit how misconfigurations, excessive permissions, and data exposure combine to create a path to critical assets.

Microsoft Defender for Cloud correlates posture, identity, data, and runtime signals to identify which risks are truly exploitable. A misconfigured storage resource on its own may appear low priority. However, when it is exposed to the internet, combined with excessive access permissions, and connected to sensitive data, it becomes part of a clear attack path that can be used to compromise the environment.

What this means: Security teams can prioritize real attack paths instead of individual findings, helping to reduce alert fatigue and improve remediation speed and precision.

2. Continuously validate and act on risk across the lifecycle

Security needs to operate continuously across development, runtime, and operations, spanning both the application and the cloud environment it runs in. Defender for Cloud connects insights across code and infrastructure definitions, cloud configuration and runtime context, application and API layers, and security operations workflows through Defender XDR.

A vulnerability identified before deployment can be tracked through to runtime, where it is evaluated in the context of the running environment and surfaced in security operations if it is determined to be exploitable.

What this means: Organizations can continuously validate risk and respond more effectively by connecting development, cloud environments, and security operations.

3. Reducing complexity across fragmented cloud and application security workflows

As environments scale, fragmented tools and workflows make it difficult to understand how risks connect and where to focus first. When cloud infrastructure and application security are managed separately, investigation becomes slower and more manual.

Defender for Cloud helps bring these signals together in a single investigative flow, where risks can be analyzed across configuration, runtime context, application behavior, and identity exposure.

Instead of switching between separate tools, security teams can investigate a single incident across its initial misconfiguration, runtime impact, application behavior, and identity exposure, a more connected experience.

What this means: Security teams can investigate faster, prioritize risk more efficiently, focus on what matters most, and respond more quickly across fragmented cloud and application environments.

What this signals for security leaders

The Frost Radar offers a signal for where cloud security is headed: toward platforms that connect context across cloud and application environments so teams can prioritize the risks most likely to be exploited and reduce exposure faster. Security leaders should now ask:

• Can the platform correlate signals across identity, endpoints, data, cloud, runtime, and applications?
• Does it span the full code-to-cloud lifecycle—and reach into the SOC?
• Can it prioritize risk based on exploitability—not just severity?
• Does it bring cloud detection and response together with application detection and response?
• Can it scale across multicloud and AI environments?

These are the capabilities that define the next generation of cloud and application runtime security.

Bottom line

Frost & Sullivan’s 2026 CARS analysis reinforces a clear shift: cloud security is moving from fragmented visibility to unified, contextual risk management across the entire lifecycle—and across both the cloud and the application layer.

Microsoft’s position as a visionary leader in the Frost Radar reflects this shift—bringing together posture, runtime, identity, endpoints, data, and application signals into a connected platform that helps organizations prioritize and reduce risk continuously.

Learn more

• Read Frost & Sullivan’s 2026 Frost Radar™ for Cloud/Application Runtime Security to see how leading vendors are evaluated—and how the category is shifting toward unified cloud and application runtime risk operations.
• Explore Microsoft cloud security solutions to see how unified posture management, risk prioritization, and protection across the application lifecycle can help reduce cloud risk.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post Microsoft named a leader in the Frost Radar for cloud and application runtime security appeared first on Microsoft Security Blog.

For years, planning for post-quantum cryptography (PQC) was framed as a future problem: important, inevitable, but distant. That perspective is evolving as technology advances and organizations prepare for the scale and complexity of the transition ahead. At Microsoft, we are acting on this shift by bringing our quantum-safe timeline forward so organizations can begin the transition earlier and with greater confidence.

Advances in quantum research and development have shifted the risk horizon. We believe cryptographically relevant quantum computers could arrive sooner than previously expected—and the work required to prepare is significant so organizations need to start now.

Recent government actions, including United States¹ and French² guidance to adopt quantum-safe cryptography as early as 2030 in certain high-risk systems, reflect the same conclusion: preparing for this transition is already underway.

This is a recognition that the transition to quantum-safe cryptography is a multi-year engineering effort that benefits from early planning and action, and delaying that work increases both cost and risk. This reinforces our decision to bring the work forward.

The quantum capabilities are accelerating. The time to respond is now.

Accelerating our timeline

In response to these shifts, we are accelerating the Microsoft Quantum Safe Program (QSP) timeline and the goal is to transition products and services to PQC by 2029.

We are also incorporating PQC requirements into our Secure Future Initiative (SFI). This brings quantum-safe readiness into the same disciplined engineering framework we use for other critical security outcomes: clear ownership, measurable milestones, and transparent progress. Embedding these capabilities into our platforms empowers customers to move sooner and more confidently.

What “accelerating” means in practice

Accelerating our timeline means pulling forward key engineering work so new standards can be adopted earlier and modernization can begin well ahead of broad quantum impact.

Our priorities fall into three areas:

1. Upgrade network cryptography (data in transit)

Modernizing network cryptography is a prerequisite for post-quantum adoption. As an example, adopting TLS 1.3 establishes a baseline that enables hybrid and post-quantum key exchange as standards mature.

What this looks like: Critical endpoints negotiate TLS 1.3 by default, with legacy protocol use reduced or eliminated wherever possible.

2. Build crypto-agility for stored data (data at rest)

Crypto-agility—the ability to change cryptography without redesigning systems—enables the safe, timely adoption of new cryptographic standards. This requires making cryptographic settings configurable outside of the application, standardizing key management and rotation, and eliminating hard-coded algorithms.

What this looks like: Cryptographic algorithms can be updated with minimal application changes and limited service disruption. You can learn more about crypto-agility here. 

3. Modernize cryptographic trust chains (identity, signing, certificates)

The most complex work is securing the chains of trust that underpin software, devices, and services at scale. That includes code signing, certificate issuance, key protection, and update pipelines.

What this looks like: This includes hardware-backed key protection, updated certificate lifetimes and policies, and auditable signing and issuance processes for critical trust anchors, with a transition to PQC algorithms as they become available.

What this means for our customers

Accelerating the timeline doesn’t change the core challenge: for most organizations, the hardest part isn’t selecting post-quantum algorithms. It’s understanding and updating where cryptography already exists across apps, services, networks, identities, certificates, and hardware.

Bringing this work forward means Microsoft can help organizations begin that process sooner, starting with an inventory-first approach to identify, prioritize, and modernize cryptographic dependencies with greater confidence.

We will continue to share technical guidance and operational best practices to help organizations adopt quantum-safe cryptography with confidence as they move from planning into execution.

Microsoft moving earlier allows organizations to align to that same timeline, one that reduces risk while maintaining operational continuity.

What we are hearing from customers and partners

Across industries and regions, organizations are already taking steps, with several consistent themes emerging:

• The future of security is agile and the transition is iterative.

Organizations are designing for change. Building crypto‑agility into systems delivers long-term resilience so new cryptography standards can be adopted over time without redesigning systems.

• Long-lived, sensitive data requires earlier protection.

Organizations are prioritizing data with long confidentiality lifetimes, recognizing that encrypted data captured today could be exposed in the future (“harvest now, decrypt later”) as cryptographic capabilities evolve.

• Preparation delivers immediate value.

Organizations that begin with cryptographic discovery and lifecycle management consistently uncover existing gaps that require attention today, independent of quantum risk.

• The hardest problem isn’t quantum—it’s complexity.

Most organizations lack clear visibility into where cryptography exists across applications, infrastructure, and legacy systems, making discovery and prioritization the primary challenge.

These signals shape how we are approaching quantum safety at Microsoft and how we support and empower all organizations in their readiness.

What to do now

Organizations do not need to wait; there are steps you can take today to begin the transition:

• Align on strategy: Define ownership, scope, and milestones for a multi-year cryptography transition.
• Design for change: Build crypto-agility into new systems so future standards shifts are updates, not fire drills.
• Begin with inventory: Create and maintain a living cryptographic inventory to identify, prioritize, and modernize dependencies.
• Modernize protocols: Adopt modern standards such as TLS 1.3 as a baseline across client and server systems.

Looking ahead

The Microsoft Quantum Safe Program (QSP) goes beyond future cryptography. It is part of a broader effort to strengthen long-term resilience across identity, infrastructure, data, and supply-chain security—bringing this work into the systems and platforms organizations rely on daily.

Our goal is straightforward: ensure that Microsoft platforms and services can adopt new cryptographic standards quickly and safely as they mature, so organizations can move at the same pace without disrupting their operations.

Microsoft will continue to share progress and practical guidance to help organizations plan, prepare, and move into execution as standards and cyberthreats evolve. By starting now, organizations can reduce risk today and be better prepared for what comes next.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

¹Securing the nation against advanced cryptographic attacks, whitehouse.gov. June 22, 2026.

²France to stop certifying products without quantum-safe encryption, Reuters. June 16, 2026.

The post Accelerating the quantum-safe timeline appeared first on Microsoft Security Blog.

Codename MDASH helps teams discover and remediate complex vulnerabilities

Codename MDASH is a multi-model agentic scanning system designed to discover, validate, and help remediate software vulnerabilities across complex environments. MDASH orchestrates a panel of specialized AI agents that reason through proprietary code and systems, helping security teams surface elusive vulnerabilities quickly and systematically. For example, when security teams use MDASH to scan a complex application, it can identify and validate a previously undetected vulnerability in the underlying code and systems, and route it into Microsoft Defender workflows and engineering pipelines for remediation. This closed loop connects discovery, validation, and remediation across the Microsoft stack. Sign up to follow codename MDASH and join the private preview to surface and validate hard-to-find vulnerabilities with multi-model AI.

Microsoft Defender extends endpoint protection to local AI agents

Microsoft Defender now discovers more than 25 types of local AI agents and Model Context Protocol (MCP) servers across managed Windows and macOS devices. Defender also protects at runtime: if a developer using a popular coding agent like GitHub Copilot Command-Line Interface (CLI) or Claude Code is targeted by a prompt injection attempts, Defender detects and blocks it before the malicious action executes. From there, security teams can investigate agent exposure across their environment with Advanced Hunting. These capabilities are now in preview.

Microsoft Entra Backup and Recovery restores critical identity data

Microsoft Entra Backup and Recovery is now generally available, delivering Microsoft-managed, always-on backups native to your environment that are protected from deletion or modification. Security teams gain clear visibility into what changed across their tenant and can back up core directory objects, compare and restore to previous timestamps, and configure Conditional Access policies to protect against permanent deletion. Together, these capabilities protect your tenant, helping you minimize downtime and recover quickly from accidental changes and security compromises. Strengthen identity resilience with rapid recovery capabilities in Microsoft Entra.

Microsoft Defender protects open-source relational databases on AWS RDS

Microsoft Defender for Cloud now extends database threat protection to open-source relational databases on Amazon Web Services (AWS) Relational Database Service (RDS). Now generally available, built-in threat detection identifies anomalous access patterns and brute-force attempts, while automated sensitive data discovery helps teams understand where high-risk data resides. These insights, combined with integrated investigation across Microsoft Defender, help teams prioritize and respond to database risks more effectively. Detect threats and discover sensitive data across Azure and AWS with Microsoft Defender.

Greater flexibility over data security insights with Microsoft Purview customizable reports

Microsoft Purview customizable reports, now generally available in Data Security Posture Management (DSPM), give teams greater control and flexibility to tailor reporting views, analyze trends, and quickly surface the insights that enable faster, more informed decisions. Choose from out-of-the-box reports or create custom reports tailored to your organization’s specific needs, with easy options to export and share insights across teams and stakeholders. For example, security teams can create role-specific reports that highlight high-risk data exposure trends to guide policy decisions. Learn how to customize reporting experiences to uncover your critical data security insights.

Broader visibility with expanded multi-cloud coverage in Defender for Cloud

Microsoft Defender for Cloud is expanding multicloud coverage and visibility across AWS and Google Cloud, adding support for approximately 90 additional resource types and more than 200 new security recommendations. Security teams can better understand their attack surface with broader visibility across cloud-native applications, identities, data services, and workloads. Across multicloud environments, teams can better assess security posture and prioritize remediation based on exposure context, compliance posture, and business criticality to reduce risk more effectively. Gain broader visibility and prioritize risk across multicloud environments with Defender for Cloud.

Prioritize risk with unified identity risk score

A new unified identity risk score combines signals from across Microsoft Security into a single, explainable measure of an identity’s risk. It brings together behavior, access patterns, and threat intelligence for all related accounts, sessions, and applications to provide a complete view of risk. The moment an identity acts suspiciously, the score helps your team cut through the noise, prioritize what’s urgent, and can automatically trigger Conditional Access policies to enforce protection at the point of access. Prioritize identity risk and enforce protection in real time with the new unified identity risk score.

Security innovations purpose built for developers

To help developers secure code, agents, and models while giving security teams consistent visibility and control from development through runtime, Microsoft is integrating security into the tools and platforms developers already use. Organizations can use the new security tools and capabilities announced at Microsoft Build 2026 to innovate faster and scale AI adoption without sacrificing security. Read more about the Build 2026 security announcements.

Stay In the Loop

Microsoft Security continually ships meaningful innovations across our portfolio and research-driven insights and reports for the security community. In the Loop posts are your reliable source of what’s new across Microsoft Security and what it means for your security strategy. Check back for the next drop.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post ​​What’s new in Microsoft Security: June 2026 appeared first on Microsoft Security Blog.

Frost & Sullivan’s 2026 Frost Radar™ for Cloud-Native Application Protection Platforms (CNAPP) reflects this shift. The report highlights how CNAPP is evolving from a collection of posture and workload capabilities into a unified cloud risk operations platform—one that correlates signals across code, cloud, runtime, and SOC workflows to prioritize and reduce risk continuously. Within this evolving market, Microsoft is positioned among leading CNAPP vendors—reflecting alignment with where the category is heading.

Why CNAPP is being redefined

The Frost Radar makes a clear point: CNAPP is no longer about visibility or compliance—it is becoming an operational platform for reducing risk.

Modern environments introduce complexity across:

• Multicloud and hybrid infrastructure.
• Rapid development and continuous deployment.
• Containers, serverless, and APIs.
• AI-powered workloads.

This complexity exposes the limits of traditional tools.

Organizations now require platforms that can:

• Correlate posture, runtime, identity, and data signals.
• Prioritize risk based on exploitability—not severity alone.
• Integrate security across development and operations.
• Support faster investigation and response.

This is the shift: from detecting issues to operationalizing risk reduction across the application lifecycle.

What distinguishes leading CNAPP platforms

Frost evaluates CNAPP providers based on growth and innovation—but more importantly, on how effectively they help organizations manage risk.

According to the report, five themes define the next generation of platforms:

• Platform unification over point solutions.
• Code-to-cloud-to-SOC integration.
• Risk prioritization based on exploitability.
• Correlation across identity, data, and application context.
• Expansion into AI-powered workloads.

These capabilities represent a shift from fragmented visibility to connected, contextual risk management.

How Microsoft aligns with CNAPP’s next phase

1. Correlating risk across identity, endpoints, data, and cloud

Most security tools surface findings. Fewer connect them meaningfully. Modern attacks exploit the combination of misconfigurations, excessive permissions, and data exposure—not isolated issues. Microsoft Defender for Cloud correlates posture findings with identity, data, and runtime signals—helping surface risks that are exploitable. A misconfigured storage resource on its own may not appear critical. But when combined with excessive access permissions and the presence of sensitive data, it can create a clear attack path.

What this means: Security teams can prioritize real attack paths instead of individual findings, reducing alert fatigue and improving remediation speed and precision.

2. Extending security from code to cloud to SOC

Security must operate continuously across development, runtime, and operations.

Defender for Cloud connects:

• Code and infrastructure-as-code scanning.
• Cloud posture and runtime protection.
• Security operations and response workflows.

A vulnerability identified in infrastructure-as-code before deployment can be tracked through to runtime—where it is validated against real-world behavior and surfaced in security operations if actively exploitable.

What this means: Organizations move from fragmented workflows to continuous risk validation and response across the lifecycle.

3. Reducing complexity across fragmented security workflows

As environments scale, tool sprawl limits visibility and slows response. Microsoft delivers CNAPP capabilities as part of a connected platform—integrating posture management, workload protection, identity, data, and threat detection across multicloud environments. Instead of switching between separate tools, security teams can investigate a single incident across initial misconfiguration, runtime impact, and identity exposure, enabling a more connected experience.

What this means: Security teams can investigate faster, prioritize risk more consistently, and reduce exposure across fragmented cloud environments.

Where security leaders focus next

The Frost Radar offers a signal for where cloud security is headed: toward platforms that connect context across cloud environments so teams can prioritize the risks most likely to be exploited and reduce exposure faster.

Security leaders should now ask:

• Can the platform correlate signals across identity, end points, data, cloud, and runtime?
• Does it span the full code-to-cloud lifecycle?
• Can it prioritize risk based on exploitability—not just severity?
• Does it integrate with SOC workflows for faster response?
• Can it scale across multicloud and AI environments?

These are the capabilities that define the next generation of CNAPP.

Bottom line

Frost & Sullivan’s 2026 CNAPP analysis reinforces a clear shift: Cloud security is moving from fragmented visibility to unified, contextual risk management across the entire lifecycle. Microsoft’s position in the Frost Radar reflects this shift—bringing together posture, runtime, identity, end points, and data signals into a connected platform that helps organizations prioritize and reduce risk continuously.

Learn more

• Read Frost & Sullivan’s 2026 Frost Radar™ for Cloud-Native Application Protection Platforms (CNAPP) to see how leading vendors are evaluated—and how the category is shifting toward unified cloud risk operations platforms.
• Explore Microsoft cloud security solutions to see how unified posture management, risk prioritization, and protection across the application lifecycle can help reduce cloud risk.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Microsoft Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post CNAPP evolution: How Microsoft aligns with leading cloud risk management platforms appeared first on Microsoft Security Blog.

Why security has become a strategic enabler for AI‑powered growth 

These customer stories highlight how security is no longer a supporting function—it’s a strategic enabler of growth, speed, and trust. As AI accelerates decision-making and reshapes how work gets done, leaders must modernize without increasing risk or slowing the business. The experiences of these forward-looking organizations reflect the realities many companies face: gaining consistent visibility across complex environments, moving faster while maintaining trust, meeting governance and compliance expectations that expand with AI adoption, and driving operational efficiency through automation. These examples will show how the right security foundation allows organizations to scale AI with confidence—turning protection into a competitive advantage, not a constraint.  

First, we’ll take a closer look at St. Luke’s University Health Network. 

How St. Luke’s is accelerating efficiency and threat response with AI 

St. Luke’s identified a critical gap in unified, real-time visibility across its security tools, limiting its ability to detect and stop threats early. The organization needed a way to see across their entire landscape and respond to threats as they emerge. To modernize and unify security operations, St. Luke’s turned to Microsoft Security Copilot to supercharge analyst productivity and help its Security Operations Center (SOC) teams operate at scale. 

By connecting Microsoft Defender and Microsoft Sentinel, St. Luke’s gains a single, AI-powered view across endpoints, identity, email, and cloud workloads—helping analysts move faster, correlate cyberthreats more effectively, and shift from reactive response to proactive, predictive defense. With AI embedded directly into daily workflows, teams can identify risks in real time, uncover gaps in visibility, and make more informed decisions with greater precision.

Streamlining workflows and automating protection

At the same time, Security Copilot agents are transforming how the SOC operates by automating time-consuming tasks like alert triage and vulnerability remediation. This reduces noise, accelerates investigations, and frees analysts to focus on real threats and strategic work. The result is a more efficient, collaborative, and resilient security operation built for today’s increasingly complex threat landscape. With Microsoft Security Copilot, St. Luke’s has:

• Unified visibility across Defender and Microsoft Sentinel eliminates silos and accelerates threat response.
• AI-powered insights help analysts detect, investigate, and act on cyberthreats in real time.
• Security Copilot agents automating routine tasks, with Security Triage Agent saving up to 200 analyst hours each month.
• Advanced phishing triage reduces false positives and improves decision confidence.
• Centralized workflows improve collaboration, reporting speed, and overall SOC efficiency.

St. Luke’s sees its investment in Security Copilot as the foundation for a self-improving security ecosystem. AI-powered security means the team stays ahead of both technological and business changes, ensuring that St. Luke’s remains resilient in the face of evolving threats. To learn more about how St. Luke’s is modernizing and unifying security operations with Microsoft Security Copilot, watch the customer video or read the full St. Luke’s customer story.

How ManpowerGroup is securing a global workforce with a unified platform 

ManpowerGroup is modernizing toward a unified, cloud-based security platform to protect a highly distributed workforce, addressing identity-centric risk and complex compliance requirements as AI becomes embedded in everyday work. Their experiences show how organizations can use Microsoft Security to secure the foundation of AI transformation, end to end. 

As ManpowerGroup scaled globally, its longstanding mix of security tools became more difficult to manage, driving complexity, inconsistent controls, and slower response as cyberthreats and regulatory demands increased. 

To reduce tool sprawl, ManpowerGroup deployed Microsoft 365 E5 for the real-time identity, endpoint, email, and cloud prevention, detection, and response capabilities of Microsoft Defender, plus the cloud-native security information and event management (SIEM) and security orchestration, automation, and response (SOAR) performance of Microsoft Sentinel. 

By deploying Microsoft 365 E5, ManpowerGroup reduced security complexity, cut integration timelines from weeks or months to hours or days, unified global security operations, and built an AI-ready security foundation. To see how this platform approach is supporting secure, agile operations worldwide, watch the customer video read the full ManpowerGroup story. 

A repeatable playbook for securing AI at scale 

While these customers operate in very different environments, their paths to securing their organization and adopting (or preparing to adopt) AI followed the same core pattern—one that other organizations can adopt as they modernize. Both started by anchoring security decisions in business risk, then unified signals across cloud, data, identity, and operations, and finally automated guardrails so protection could scale alongside AI-powered work. These experiences point to a clear, repeatable approach for security and adopting AI without slowing business: 

• Lead with risk and business value. Clearly define what must be protected—and why—so security enables AI adoption rather than constraining it. 
• Unify visibility across the environment. Connect cloud, identity, data, and security operations (SecOps) signals into a single operational view to reduce blind spots. 
• Make governance real, not aspirational. Operationalize classification, labeling, data loss prevention, and policy enforcement, so protections are consistent by default. 
• Harden posture continuously. Use continuous configuration management and drift detection to prevent misconfigurations as environments evolve. 
• Automate outcomes at scale. Streamline response and compliance reporting so security and governance improve without increasing headcount. 

This approach helped both organizations move faster with confidence—and offers a practical blueprint for others looking to secure the foundation of AI transformation. 

What Frontier firms get right in the AI era 

These stories point to a broader pattern emerging among leading organizations. “Frontier firms” refers to organizations that lead in the AI era by pairing speed with trust. They move quickly—but not recklessly—because security is treated as a foundational capability, not an afterthought. For these organizations, protection is built into how work gets done: governance that scales as AI adoption grows, posture that remains resilient as environments change, and controls that operate continuously in the background. Security becomes the primitive that allows AI to be deployed with confidence, not constraint. 

These customers exemplify what this looks like in practice. And through their stories, we gain a playbook that other organizations can deploy with confidence. By modernizing security as a platform—connecting visibility, governance, posture management, and automation—organizations can enable AI-powered work while strengthening trust across data, identities, cloud environments, and more. These customer stories show that in the AI era, organizations that treat security as a strategic foundation will be best positioned to lead, adapt, and compete in an AI-powered world. Learn more about how Microsoft Security helps organizations secure AI-powered work at scale. 

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To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.  

¹Secure agentic AI for your Frontier Transformation, Microsoft Security blog. March 9, 2026.

The post Microsoft Security success stories: How St. Luke’s and ManpowerGroup are securing AI foundations appeared first on Microsoft Security Blog.

Microsoft Purview visibility now extends to Anthropic’s Claude

Security and compliance teams can now detect and investigate Claude usage alongside other cloud applications in their broader AI ecosystem. The new Claude Compliance API for Microsoft Purview delivers centralized visibility and oversight for Claude Enterprise activity enabling Microsoft Purview to provide insights on Claude interactions and audit log signals. This integration will provide visibility across Claude Enterprise, extending the Microsoft Purview experience and helping your teams protect sensitive data across your AI estate.  

New data security posture management experience in Microsoft Purview

The new Microsoft Purview Data Security Posture Management (DSPM) experience is now generally available. This solution unifies and streamlines DSPM across scenarios, from discovery to protection, all the way to remediation, allowing teams to investigate risks and take actions on the same workflow. The new experience delivers goal-oriented flows, deeper remediation, expanded reporting, and third-party visibility. Your teams can efficiently discover sensitive data, assess risk, and take action at scale.

Microsoft Purview Data Security Investigations extends investigative depth with custom examinations

Microsoft Purview Data Security Investigations now includes optical character recognition (OCR) and custom examination capabilities to extend investigative depth. OCR extracts text from images, bringing previously inaccessible visual content into scope for AI-powered deep content analysis. In addition to existing examination types that identify credentials, risk, and personally identifiable data, and help inform mitigation, investigators can define their own analysis with custom examination, enabling more tailored and flexible investigations based on their unique needs. 

Microsoft Entra ID Account recovery securely restores account access

Microsoft Entra ID Account recovery is an advanced authentication recovery mechanism that enables users to regain access to their organizational accounts when they’ve lost access to all registered authentication methods. Unlike traditional password reset capabilities, Account recovery focuses on identity verification and trust re-establishment prior to replacement of authentication methods rather than simple credential recovery.

Windows 365 for Agents delivers a secure AI agent execution environment

Windows 365 for Agents, now expanding in public preview, and Microsoft Agent 365 work together to provide a consistent, secure environment to run and govern agents. Agent 365 determines the work an agent is authorized to do, using shared organizational policies and identity to govern agent behavior and access. Windows 365 for Agents defines where an agent executes the work, providing Cloud PCs that enable agents to operate their own desktops and applications within a fully managed and auditable environment. Read our blog for more details.

Stay In the Loop

Microsoft Security continually ships meaningful innovations across our portfolio and research-driven insights and reports for the security community. In the Loop posts are your reliable source of what’s new across Microsoft Security and what it means for your security strategy. Check back for the next drop and connect with us at Microsoft Build, June 2-3, 2026, in San Francisco, to hear directly from Microsoft Security experts and learn more about today’s releases.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post What’s new in Microsoft Security: May 2026 appeared first on Microsoft Security Blog.