Monthly news - July 2026
Microsoft Defender Monthly news - July 2026 Edition This is our monthly "What's new" blog post, summarizing product updates and various new assets we released over the past month across our Defender products. In this edition, we are looking at all the goodness from June 2026. We are now including news related to Defender for Cloud in the Defender portal. For all other Defender for Cloud news, have a look at the dedicated Defender for Cloud Monthly News here. 🚀 New Virtual Ninja Show episode: Redefining identity security for the modern enterprise One policy engine to govern them all: Securing agentic AI with Microsoft Purview Building a modern detection pipeline with ContentOps Securing local AI agents with Microsoft Defender Microsoft Defender: Extending critical protection for emerging threats in Team Weekly Security News: We publish a short 1ish minute video every week with updates across our Microsoft Security stack. Subscribe to our YouTube channel, so you don't miss the next episode. Actionable threat insights (find all of them here) Securing AI agents: When AI tools move from reading to acting Chromium extension uses AI‑related branding to redirect browser search Photo ZIP campaign targeting hospitality industry delivers Node.js implant for persistent access Microsoft Defender Two Workbooks capabilities in the unified Microsoft Defender portal moved to GA: Advanced Hunting connector - build custom dashboards directly on top of Advanced Hunting (XDR) dat. Query XDR tables and visualize them in Workbooks for richer investigations and reports. Workspace filter / multi-workspace experience - scope and filter workbooks by workspace, with workspace selection integrated into the workbook itself rather than relying on the global selector. MTO Tenant Groups let MSSPs and large enterprises organize their multitenant view in Microsoft Defender by grouping tenants logically (e.g., by region, business unit, or customer cohort). Learn more here. Custom Detections support in Microsoft Sentinel Repositories. Custom Detections can now be managed as code in Microsoft Sentinel Repositories, the same way customers already manage analytic rules, playbooks, parsers and workbooks. Detection engineers connect a GitHub or Azure DevOps repo to their workspace; Custom Detections placed in the repo are reconciled on every commit. A standalone Bicep path via the Microsoft Security Bicep extension lets teams deploy from any CI/CD pipeline (ADO Pipelines, GitHub Actions, custom runners). (General Availability) The following advanced hunting schema tables are now generally available: The CloudAuditEvents table contains information about cloud audit events for various cloud platforms protected by the organization's Defender for Cloud. The CloudDnsEvents table contains information about DNS activity events from cloud infrastructure environments. The CloudProcessEvents table contains information about process events in multicloud hosted environments. (Public Preview) The AgentsInfo table in advanced hunting is now available in preview. The AIAgentsInfo table is transitioning to this new table, which provides a unified schema that supports agent inventory and governance for all agent types, including Copilot Studio, Microsoft Foundry, Microsoft 365 Copilot, third-party, and endpoint-discovered agents. Microsoft Agent 365 customers should use the AgentsInfo table today. The AIAgentsInfo table remains accessible until July 1, 2026. Update your queries to use AgentsInfo before this date. For more information, see Advanced hunting schema - Naming changes. For all other Sentinel News, have a look at the "What's new in Microsoft Sentinel blog post - June edition" Identity Security (Public Preview) The Identity Security dashboard now includes a new Human identities card that shows your human identities by source (Entra ID, SaaS, and on-premises), giving you a single view of where your human identities live. For more information, see Identity Security dashboard. (Public Preview) On the Coverage and maturity page, the Review and improve coverage side panel for SaaS Identities now includes an Observed column and a Show Only Observed Applications toggle. By default, the panel shows only SaaS applications detected in your environment. Turn off the toggle to see other supported SaaS applications you can onboard to expand your identity coverage. For more information, see Coverage and maturity. New alerts were added to the Defender for Identity security alerts related to Microsoft Entra ID, Active Directory as well as other identity providers. For a full list of those new alerts, check out our documentation. Recent ShinyHunters attacks on Salesforce show how OAuth tokens and connected apps are being weaponized to bypass MFA at scale. The upgraded Salesforce connector for Defender for Cloud Apps helps detect these attacks faster, with richer connected-app context and investigation-ready signals. Customers already using the connector are advised to enable the additional events in the Salesforce console for tighter protection, and eligible customers not yet using it are advised to connect Salesforce. Learn more. Microsoft Defender for Endpoint / Microsoft Defender Vulnerability Management (Public Preview) Local AI agent discovery: as part of the Defender AI agents experience, Microsoft Defender now automatically discovers supported local AI agents running on onboarded Windows & macOS devices. Discovered agents appear as assets in the AI agent inventory, exposure map, and advanced hunting, giving security teams visibility into local AI agent usage across the organization. For more information, see Discover local AI agents. (Preview) Local AI agent runtime protection on Windows endpoints is now available in public preview. Microsoft Defender inspects the agent loop (user prompts, tool calls, and tool responses) and can block risky activity before it executes, helping stop prompt injection and unsafe agent actions at the device level. Blocked and audited events appear as alerts in Microsoft Defender to support incident correlation and investigation workflows. The new version of the Defender deployment tool for Windows streamlines onboarding and enhances security by: Bundling the onboarding package directly into the tool's executable. Generating a key during deployment package creation that is required for running the tool. Enabling users to configure an expiry date for the package to reduce the risk of unauthorized use. In addition: You have the option of downloading the package as either an .exe or a .zip file, whichever best suits your organization's needs. A new Deployment packages page in the Defender portal facilitates management of downloaded packages by providing centralized visibility into all the packages and their current status. Now generally available: Selective Response Actions enables organizations to tailor high-impact security operations on devices during onboarding. It provides precise control over how response actions are applied on Tier-0 systems and other high-value assets, helping maintain operational stability while delivering strong protection. The new exposure score model in Defender Vulnerability Management is now generally available. This model improves risk prioritization and recommendation impact accuracy by incorporating exploit prediction data (EPSS) and asset context factors such as internet-facing status and criticality. More details here. Microsoft Secure Score now includes the Reduce unnecessary inbound internet exposure on internet-facing devices recommendation, which helps identify devices that are accessible from the public internet and may represent unnecessary attack surface. This recommendation provides centralized visibility into internet-facing devices across the environment. Many predefined SaaS application classification rules were added to the critical assets list. Have a look at our documentation for the full list. These classifications require onboarding to Microsoft Defender for Cloud Apps.Empowering SOC Analysts: Investigating Identity Threats with Microsoft Defender XDR
Identities have been a top threat vector forever. However, the rise of cloud identity attacks and an ever increasingly complex digital estate has made a tough problem even harder. Securing identities has always required a close partnership between two different functional teams – the identity and access management teams that are responsible for managing, authenticating, and authorizing user access to protected systems and data; and the security teams that detect and respond to threats across the entire digital estate. Nowhere is this more apparent than during a security incident. Let’s take a look at a common attack type like this phishing email example below: While this is a straightforward scenario, it’s still extremely effective as many organizations aren’t equipped to protect against it. The 2024 Verizon Data Breach Investigation report detailed how the median time for an attacker to access data from phishing is now just 60 seconds, giving the security team little time to triage alerts across email, identity, and endpoints, coordinate with the IAM team to disable the user and reset the password, and clean up any affected devices and inboxes. This is where implementing an integrated Identity Threat Detection and Response (ITDR) solution comes in. Our solution breaks down the existing silos between your identity and security teams by natively integrating our IAM solution, Microsoft Entra ID, and our identity threat protection solution, Microsoft Defender for Identity into our Extended Detection and Response (XDR) platform. Our ITDR offering is unique in that it delivers robust ITDR capabilities where your teams already work today. This means empowering the SOC to investigate identity alerts directly within Defender while also surfacing necessary insights from those investigations for Identity Admins directly within the Entra experience. Enhancing XDR with ITDR Identity is a core pillar of our XDR solution. Capitalizing on Microsoft’s leadership in both Identity and Access Management (IAM) and security, Defender correlates identity data and insights with Endpoint, Cloud, SaaS app and collaboration alerts to help security professionals better understand the full scope of security threats without spending hours triaging and correlating alerts. Customers benefit from the following within the Defender experience: 1. Enriched visibility across the identity fabric The ITDR dashboard provides the SOC with a single, prioritized view of Identity-specific security information and recommendations. Pulling relevant alerts and insights from across their identity footprint, this pane helps SOC teams better understand their identity posture and quickly manage potential identity-related security risks. Additionally, the recently updated identity inventory provides visibility into all the identities within their fabric including human and non-human, on-premises or in the cloud, from Microsoft or another provider. Each one of those identities also has a corresponding identity page which offers even more insights into the identity itself and allows the SOC to take action on that identity, right from the experience. 2. Proactive Identity posture and prevention The robust posture recommendations within Microsoft Security Exposure Management include Identity-specific posture recommendations (ISPM’s) that range from spotting common misconfigurations to helping customers address vulnerabilities across Active Directory, Entra ID and other common identity fabric elements, before they can be exploited. This is further enriched with attack path modeling, which provides a prioritized queue of possible attack paths that could be exploited by a threat actor. This helps the SOC and identity teams understand the entire scope of vulnerabilities—from initial access to reach critical data—and work together to prioritize the highest priority exposures. Again, because of the native integration between Entra ID and Defender the recommendations surfaced to identity admins and SOC professionals are consistent, helping the two teams work in unison to strengthen their overall identity. Defender for Identity provides dedicated sensors for Domain Controllers, Active Directory Federation Services (ADFS), Active Directory Certificate Services (AD CS) and Entra ID Connect to provide comprehensive visibility into on-premises identity environments while Entra ID does the same for cloud identities. 3. Incident-level visibility Microsoft Defender uses XDR-level detections to automatically correlate all related alerts into prioritized incidents – making it easy for analysts to see which alerts are tied to a broader incident and need to be addressed first. Incidents are automatically updated if new related alerts are triggered, so analysts can be confident they’re always looking at the latest info. Incidents are also automatically enriched with identity-related insights – like recently logged on users on an endpoint, recent activity, MFA type, open incidents, Entra ID risk level, and more—so the SOC team can quickly understand the full context of a user without needing to go hunting. All of this information is synced automatically with Microsoft Entra, ensuring both the identity and SOC teams are looking at the same data. This context is also showcased within the hunting experience. Customers can hunt for emerging threats across identity and other domains right from the same pane. 4. Automated Threats Response With attackers moving laterally in just minutes, even the best security teams will be challenged to respond in time with manual processes. Microsoft Defender utilizes AI to automatically take action on in-progress attacks and prevent lateral movement. This built-in, self-defense capability uses the correlated signals in XDR, the latest threat intelligence, and machine learning backed models to accurately predict the attack path used and block an attacker’s next move before it happens with above 99% confidence. Disruption attacks only take the minimum action necessary to stop the attacker – like disabling a compromise user or containing an affected endpoint – limiting the impact on the organization and leaving the SOC and identity teams in control to complete the investigation and bring assets back online. Security professionals can take direct action on identities right from the XDR experience through actions like “Confirm user as compromised” or “Disable user,” to mitigate an active threat. These updates are reflected automatically in the Entra portal, so they work in conjunction with Entra’s risk based conditional access. That way, when an identity is confirmed as compromised by the SOC, the risk level within Entra will automatically be raised and the relevant conditional access policies will be triggered at the next login to prevent future attacks. This signal loop protects customers both proactively through continuous monitoring and zero-trust policy engine , and reactively through real-time alerts and response from both Entra ID and Defender XDR. Conclusion In today's dynamic cyber landscape and with the complexity of modern identity environments, SOC analysts require a single pane of glass view into and the ability to effectively combat identity threats. Microsoft XDR, with its integration of Microsoft Defender for Identity and Microsoft Entra ID, provides a unified platform that enhances identity threat detection, investigation, and response capabilities, across on-prem and cloud. The seamless flow of data, alerts and workflows between IAM and Security teams created by this integration closes the loop between reactive and preventative identity protection helping organizations stay ahead of adversaries and ensure the security and integrity of their systems and data.Closing the loop on container security: From code to runtime in the AI era
Containers are the backbone of modern cloud-native apps — and increasingly, the infrastructure powering AI, from AI assistants to a new wave of intelligent agents. They also blur the line between build, deploy, and runtime: a single code change can become a running workload in minutes. A misconfiguration committed in the morning can be deployed in minutes and exploited before noon. At that speed, container security can no longer be a point-in-time check, it has to work as one continuous loop. The numbers back this up. For the first time, 31% of breaches now begin with an attacker exploiting a software vulnerability — overtaking stolen credentials as the most common way in — and 15% of attack techniques are now accelerated by generative AI, with adversaries using it to find gaps and write malware faster at every stage. Source: Verizon 2026 Data Breach Investigations Report (incidents Nov 2024–Oct 2025). Over the last few quarters, Microsoft Defender for Cloud has been evolving to offer you this continuous security, end to end. Explore container security’s new capabilities across posture, shift-left, runtime, multicloud coverage, and operations. Collectively they form a more comprehensive approach to container security — one that offers security right during developing a code to a running pod across Azure, AWS, and GCP. There is a second reason why container security matters more in 2026: containers are increasingly where AI runs. Many AI workloads — from model-serving APIs to retrieval systems and intelligent agents — now live as pods on AKS, EKS, and GKE (the managed Kubernetes services from Azure, AWS, and Google), often connected to some of an organization’s most sensitive models and data. As those crown jewels move into the cluster, the same posture, code‑to‑runtime, and runtime protections described in this post extend to AI workloads. The contest is increasingly AI against AI: attackers use it to find and reach the cluster faster, while defenders use it to push back — surfacing the risks that matter most and turning runtime findings into AI‑assisted code fixes. One platform, code to runtime A container finding is not treated as an isolated issue; it is connected to the identity it runs under, the registry and code repository it came from, and the cluster where it is running - all unified under one Microsoft Defender platform. Container posture and shift-left security are now redesigned for least vulnerabilities in production Conventional container security posture offered challenges to scale: a single grouped recommendation could stack thousands of findings under one bucket, making ownership, exemptions, and risk scoring too coarse to act on. That experience is now evolved. We have rebuilt the experience so that each finding is its own recommendation — per software, per image, per container. If two CVEs in the same image belong to two different teams, they can now be triaged, exempted, and reported separately. The grouped recommendations are deprecated and will be removed on July 30, 2026, We suggest updating any automation, export rules, and ServiceNow integrations to target the new per-finding recommendations before that date. That per-finding precision becomes even more powerful once you connect each finding to its source code and to the runtime resources it impacts. Defender for Cloud — part of Microsoft Defender suite — connects this code-to-runtime chain end-to-end. For example, an image built through Azure DevOps or GitHub, pushed to ACR, ECR, Google Artifact Registry, Docker Hub, or JFrog, and pulled by AKS, EKS, or GKE is one continuous evidence chain — traceable from a running container back to the pull request (PR) and line of code that introduced the risk. With GitHub Advanced Security integrated (GA), secrets, code, and dependency findings join the same attack story. The developer-first Defender for Cloud CLI runs the same scanner locally or in any CI/CD pipeline, with consistent exit codes for gating. In this diagram, you can see how we have embedded container security at every stage of the software development lifecycle (SDLC), not just the endpoints. At Code, GitHub Advanced Security and the Defender for Cloud CLI catch secrets, vulnerable dependencies, and insecure code before commit. At Build, the same scanner runs as a CI/CD gate — in GitHub Actions, Azure DevOps, Jenkins, or Bitbucket — failing the pipeline on critical findings. At Ship, registry scanning and Gated Deployment block risky or misconfigured images at the cluster door. And at Runtime, the sensor enforces anti-malware and binary-drift policy on the live workload. No stage is left as a blind spot, and a finding can be traced forward to the running pod or backward to the developer who introduced it. Visibility without enforcement only creates backlog. Gated Deployment — a Kubernetes admission controller — uses the same vulnerability signal, you trust, to block risky images at the cluster level. It supports phased rollout (audit, then deny), targets rules by cluster, namespace, pod, image, or label, and runs across AKS (including AKS Automatic), EKS, and GKE. A newer extension gates on Kubernetes misconfigurations too. Posture practitioners also get KSPM at container granularity — Kubernetes security posture management, available through both Defender for Containers and Defender CSPM — and, on Azure, a new actionable recommendation, Upgrade Azure Kubernetes Service Version (preview), that helps you remediate vulnerabilities in AKS-managed system pods. Coverage that matches containers’ evolution Historically, many container security programs concentrated on managed Kubernetes clusters in AKS, EKS, and GKE. The 2026 reality is broader: a growing share of production runs on serverless container platforms that abstract the cluster away, many sensitive workloads sit behind private, network-isolated clusters, and platform teams increasingly standardize on hardened or distroless base images. The surfaces that were blind spots are now part of the same posture graph as everything else. Serverless compute posture is now generally available across AWS Lambda, Azure Functions, and Web Apps, while Serverless containers posture (preview) takes the same idea to Azure Container Apps, ACI, and AWS Fargate. Together, they bring more of today’s cloud-native production footprint into the same posture graph. Coverage also improves where platform teams are standardizing on locked-down environments. The long-standing gap around private EKS and GKE clusters is closed, bringing some of the hardest-to-reach environments into the same security model. Scanning now works on hardened images from Docker Hardened or Minimus, and runtime protection supports BottleRocket on EKS — with the full feature set also available in Azure Government, which matters for teams running regulated workloads. Runtime threat protection that prevents, not just detects Posture closes the door on attackers; runtime threat protection guards the room if they still succeed. The key shift is that the Defender for Containers sensor now adds prevention on top of detection. The goal is simple: stop malicious code before it runs. Anti-malware detection and prevention (GA) scans container workloads and Kubernetes nodes and, based on the policies you define, blocks malicious execution instead of only alerting. Those alerts then flow into Microsoft Defender XDR’s unified incident model. The second is binary drift detection and prevention (preview). Containers are meant to be immutable. When a process starts from a binary that was not part of the original image, that is drift — and one of the highest-signal indicators of compromise in cloud-native workloads. Defender detects drifts and, with policy enabled, can now also block the drifted process before it executes. Anti-malware and Drift policies can be scoped by cloud, cluster, namespace, image, or label, with allow-lists for legitimate cases. Anti-malware policies can alert, block, or ignore — scoped to clusters, namespaces, pods, labels, or images. Rounding out runtime protection, DNS-based threat detection (GA) catches command-and-control beaconing, DGA traffic, and exfiltration over DNS. A unified approach to container security Step back, and the bigger picture is simple. The same platform that secured your VMs and identities now extends across AKS, EKS, GKE, private clusters, serverless containers, and serverless compute. The same Code-to-Runtime chain that once tied Infrastructure as Code (IaC) findings to running infrastructure now connects Dockerfile commits — through CI/CD and any major registry — to the running pod. Admission control turns posture findings into prevention at deploy time, and runtime protection actively blocks. That is a continuous container security loop living inside Microsoft Defender — not a checklist bolted onto Kubernetes. And it rebalances the fight: as attackers use AI to find and exploit gaps faster, the durable answer is security teams using AI of their own — protecting and triaging at machine speed. If you’ve already enabled container security with Microsoft, the clearest next step is to strengthen the core lifecycle stages first: Code + build: connect GitHub Advanced Security and integrate the Defender for Cloud CLI into your pipelines so findings are caught early and CI/CD gates can fail builds before an image is pushed. Ship: stand up Gated Deployment in audit mode on a non-production cluster, tune it, then flip to deny; extend it to Kubernetes misconfigurations. Run: enable the Defender for Containers sensor, extend it to private EKS and GKE clusters, then tune anti-malware and binary-drift rules in Block mode — starting with your crown-jewel namespaces. Extend protection: turn on serverless compute posture for Lambda, Functions, and Web Apps, and enable serverless container posture for Container Apps, ACI, or Fargate.
Security Copilot RBAC for Embedded Experience in Unified Security Platform
Introduction The evolution of Security Operations Centers (SOC) is increasingly driven by AI-powered capabilities that improve efficiency, accuracy, and response time. Microsoft Security Copilot represents a significant advancement in this space by embedding AI-driven assistance directly within security platforms such as Microsoft Defender XDR, Microsoft Sentinel, and Microsoft Entra. The concept of embedded experience is central to this transformation. Rather than operating as a standalone interface, Security Copilot is integrated within existing security tools, allowing analysts to invoke AI-generated insights directly during investigations. This reduces the need for tool switching and accelerates decision-making. The purpose of this document is to define and explain the Role-Based Access Control (RBAC) model required to securely enable this embedded experience. It provides a structured understanding of how access is governed across multiple layers, how these layers interact, and how organizations can align permissions with SOC workflows while maintaining a least-privilege security posture. Understanding Embedded Experience Security Copilot in embedded mode operates within the context of the host platform. When invoked from Defender or Sentinel, it does not function independently but instead consumes data already accessible to the user. This model ensures that Copilot enhances visibility without expanding access boundaries. This behavior is governed by an On-Behalf-Of (OBO) model, where Security Copilot leverages the permissions of the authenticated user. It does not introduce new entitlements or override existing RBAC configurations. As a result, the insights generated by Copilot are always limited to what the user is already authorized to see, reinforcing Zero Trust principles and preventing unauthorized data exposure. Prerequisites for Embedded Experience To enable Security Copilot in an embedded environment, organizations must establish foundational prerequisites that ensure seamless and secure operation. First, access to underlying platforms such as Microsoft Defender XDR, Microsoft Sentinel, and Microsoft Entra must already be provisioned. Since Copilot is not a standalone data source, it cannot function without these integrations. Second, RBAC alignment across identity, platform, and service layers must be configured correctly. Misalignment can lead to incomplete results, restricted functionality, or inconsistent analyst experiences. Finally, governance processes such as access review, monitoring, and adherence to least privilege principles should be implemented. These controls ensure that Copilot usage remains compliant, auditable, and aligned with organizational security policies. RBAC Framework for Security Copilot Security Copilot adopts a multi-layer RBAC model consisting of three tightly integrated layers. These layers collectively determine whether a user can access Copilot features and what data they can retrieve. RBAC Layer Mapping RBAC Layer Role Type Purpose Example Roles Access Impact Security Copilot Platform Feature access control Determines who can use Copilot capabilities Security Copilot Owner, Security Copilot Contributor Enables use of Copilot features but does not grant data access Microsoft Entra ID Identity and directory governance Controls access to identity data and reports Security Reader, Reports Reader, Security Administrator Governs identity insights and directory visibility Service-Specific RBAC Data access control Defines access to security data within services Defender Security Reader, Sentinel Reader Determines what Copilot can retrieve and present This layered approach ensures that no single role grants full access. All three layers must align for complete functionality. Security Copilot Platform Roles Security Copilot platform roles control who can interact with the Copilot interface and execute AI-driven workflows. The Security Copilot Owner role provides administrative control over Copilot configuration, including access management and platform-level settings. This role is typically assigned to administrators responsible for governance and operational enablement. The Security Copilot Contributor role enables analysts to run prompts, perform investigations, and interact with Copilot features during daily SOC operations. However, this role does not grant visibility into security data by itself. This clear separation ensures that Copilot remains a controlled interface layer rather than a source of privilege escalation. Microsoft Entra ID Roles Microsoft Entra roles govern access to identity-related data, which is critical for security operations involving user behavior, sign-in logs, and directory insights. Roles such as Security Reader provide read-only visibility into security data, while Reports Reader enables access to reporting and analytics capabilities. In certain advanced cases, the Security Administrator role may be required for configuration-level actions. The document emphasizes avoiding excessive privilege assignment, particularly the use of Global Administrator roles for daily operations, as this conflicts with least privilege principles. Service-Specific RBAC Roles Service-level roles determine the data sources that Security Copilot can access when embedded in platforms. In Microsoft Defender XDR, roles such as Security Reader allow access to alerts, incidents, and endpoint data. In Microsoft Sentinel, Sentinel Reader provides access to log data, analytics, and incidents. In Microsoft Entra, roles like Reports Reader provide access to identity insights. Copilot cannot retrieve or analyze data beyond what these roles permit. The output it generates is always constrained to the user’s effective permissions across these services. Unified RBAC Behavior in Embedded Experience In an embedded scenario, all three RBAC layers are evaluated simultaneously. When a SOC analyst invokes Copilot in Defender, the system validates whether the user has permission to use Copilot, access identity data, and retrieve Defender-specific insights. Only when all these conditions are satisfied does Copilot provide a comprehensive output. This ensures that Copilot responses are both contextually rich and access-compliant, eliminating the risk of unauthorized data exposure while maintaining operational efficiency. Security Copilot Core Use Cases Security Copilot enables a layered set of capabilities that span both analyst interaction patterns and agent-driven execution models. These use cases collectively enhance SOC efficiency, decision-making, and operational scalability. Use Case Mapping Table Use Case Description Embedded / Agent Example Value to SOC Summarization Transforms complex alerts, incidents, and telemetry into structured, human-readable insights by correlating signals across multiple sources Summarizing a Defender XDR incident involving endpoint, identity, and cloud alerts into a unified attack narrative Reduces analyst fatigue and significantly accelerates triage by eliminating manual data aggregation Guided Response Provides contextual, step-by-step investigative guidance and recommended remediation actions based on observed patterns and threat intelligence Suggesting investigation paths in Sentinel, including pivoting to identity logs, device timeline, and lateral movement indicators Improves consistency in investigations and enables less experienced analysts to operate effectively Script Analysis Evaluates scripts, queries, and command-line activities to identify malicious patterns, errors, or optimization opportunities Analyzing PowerShell scripts or KQL queries used in threat hunting scenarios to detect obfuscation or suspicious logic Enhances detection accuracy and reduces the risk of missing critical indicators Reporting Generates structured incident summaries, executive reports, and compliance-ready documentation with contextual insights Producing incident summaries for leadership or compliance teams with both technical and business context Improves communication, supports audit readiness, and reduces manual reporting overhead Agent-Driven SOC Use Cases (Expanded Capabilities) With the introduction of Security Copilot agents, the platform extends beyond assistance into orchestrated, intelligence-driven operations across SOC workflows. Agent-Based Use Case Description Real Agent Example SOC Impact Dynamic Threat Detection Continuously analyzes telemetry to identify previously undetected or weak signals across the attack surface Dynamic Threat Detection Agent correlates signals across Defender workload telemetry to surface hidden threats Improves detection coverage and reduces the likelihood of missed attacks Threat Intelligence Correlation & Briefing Aggregates internal and external intelligence sources to generate contextual threat insights aligned to organizational risk Threat Intelligence Briefing Agent produces structured intelligence reports based on attack patterns and exposure context Enhances situational awareness and supports proactive defense strategies Advanced Threat Hunting Enables hypothesis-driven and AI-assisted threat hunting by generating queries, exploring telemetry, and correlating historical data Advanced Threat Hunting Agent builds and executes queries across Defender and Sentinel datasets for proactive investigation and telemetry exploration Accelerates threat discovery and reduces reliance on manual query development Security Analysis & Threat Prioritization Performs AI-driven analysis of security telemetry to identify high-risk patterns, prioritize threats, assess risk exposure, and recommend investigative actions Security Analyst Agent analyses password spray attacks, ransomware activity, malware campaigns, identity abuse, and other security risks by generating telemetry-driven assessments and recommendations Improves analyst productivity, prioritizes high-impact threats, and enables faster decision making Security Triage Automation Automates alert prioritization and classification by adding contextual enrichment and reducing noise Security Triage Agent / Phishing Triage Agent evaluates alerts and distinguishes between real threats and false positives Reduces alert fatigue and improves prioritization accuracy in high-volume environments End-to-End Investigation Orchestration Performs multi-step investigation by gathering signals, correlating activity, and building attack timelines Security Analyst Agent investigates incidents across identity, endpoint, email, cloud, and data signals to produce a consolidated incident narrative Reduces Mean Time to Investigate (MTTI) and ensures consistent investigation outcomes Cross-Domain Threat Correlation Connects signals across identity, endpoint, cloud, email, and data domains to identify multi-stage attack chains Agents operating across Defender, Entra, Sentinel, and Security Copilot correlate activities such as phishing leading to identity compromise and lateral movement Breaks down silos and enables holistic threat visibility across the environment Remediation & Response Enablement Identifies vulnerable assets and supports remediation workflows through contextual recommendations Agents integrated with endpoint and policy systems suggest patching actions, containment actions, and configuration changes based on detected risks Improves response effectiveness and strengthens overall security posture Each of these use cases operates within the RBAC boundaries defined earlier, ensuring secure and context-aware outputs. Mapping Use Cases to SOC Processes The four core use cases align directly with SOC operational stages, enabling a consistent and repeatable analysis model. Summarization plays a significant role during the detection and triage phase, where analysts need quick clarity on incoming alerts. Instead of manually analyzing raw data, Copilot provides a structured overview, helping analysts determine priority and relevance. Guided response becomes critical during the investigation and response phase, where decision-making speed is essential. By suggesting next steps and correlating data points, Copilot assists analysts in navigating complex attack scenarios. Script analysis supports both threat hunting and investigation, allowing analysts to validate scripts, queries, or automation logic. This reduces the risk of overlooking malicious behavior embedded in scripts. Reporting aligns with the post-incident and compliance phase, where structured documentation is required. Copilot generates summaries that can be shared with leadership or compliance teams, ensuring clarity and consistency. Together, these use cases create a continuous cycle of detection, investigation, response, and reporting, fully integrated with SOC workflows. Summary Security Copilot’s embedded experience represents a transformative shift in how AI is integrated into security operations. By embedding intelligence directly within platforms such as Defender and Sentinel, it enhances analyst productivity while maintaining strict governance controls. The three-layer RBAC model, consisting of Security Copilot roles, Microsoft Entra roles, and service-specific roles, ensures that access is both secure and compliant with least privilege principles. The On-Behalf-Of model further guarantees that Copilot does not expand access beyond existing permissions. The inclusion of structured use cases such as summarization, guided response, script analysis, and reporting enables organizations to operationalize Copilot effectively across SOC processes. When RBAC is properly aligned and integrated with SOC workflows, Security Copilot becomes a powerful enabler of faster investigations, improved accuracy, and enhanced security posture—all while maintaining strict control over data access and governance.Ignite 2025: What's new in Microsoft Defender?
This Ignite we are focused on giving security teams the edge they need to meet adversaries head on in the era of AI. The modern Security Operations Center (SOC) is undergoing a fundamental transformation, placing AI at the forefront of innovation - not just as an added feature, but as a driving force at every layer of the stack. While much attention is rightly focused on the development of security agents, we fundamentally believe that AI must also evolve the very foundation of our security solutions. This means building solutions that more effectively uncover novel threats, act dynamically to defend the organization during attacks, and reduce the workload for the security team. As organizations adopt AI at an unprecedented speed, we also want to make sure they can do so securely. To meet these security needs of the AI era, we are excited to announce a series of innovations that will help organizations shift to an autonomous defense and an agentic SOC. New agents to help scale and accelerate security operations Evolving Microsoft Defender’s autonomous defense capabilities for better protection Secure your low-code and pro-code AI agents with Microsoft Defender Today, we are taking the first step in shifting security operations from static controls to autonomous defense and from manual toil to agentic operations. But we have an ambitious vision to augment and evolve these AI capabilities and agents across the entire SOC lifecycle and are excited to share some of that vision, as shown in the below graphic, with you at Microsoft Ignite. The Agentic SOC: Scaling expertise and accelerating defense We are excited to introduce four new Security Copilot agents in Microsoft Defender that bring autonomous intelligence across different stages of the SOC lifecycle. These agents combine context, reasoning, and complex workflows to help defenders anticipate attacks sooner, detect smarter, and investigate faster than ever before. Security Alert Triage Agent: In March 2025, we introduced the Security Alert Triage Agent, built to autonomously handle user-submitted phishing reports at scale. The agent reviews and classifies incoming alerts, resolves false positives and escalates only the malicious cases that require human expertise. Early data shows that analysts working with the agent caught up to 6.5x more malicious emails compared to professional graders. Today, we’re excited to announce that the agent’s triage capabilities will soon extend beyond phishing to cover identity and cloud alerts. Secondly, we are also improving our phish admin reporting process with a new agentic email grading system. It replaces a manual review process with advanced large language models and agentic workflows to deliver rapid, transparent verdicts and clear explanations to customers for every reported email. Learn more about the agentic email grading system. Threat Hunting Agent – this agent reimagines the investigation process. Instead of requiring analysts to master complex query languages or sift through mountains of data, the Threat Hunting Agent enables natural language investigations with contextual insight. Analysts can vibe with the agent by asking questions in plain English, receive direct answers, and be guided through comprehensive hunting sessions. This levels up the current NL2KQL experience by enabling analysts to explore patterns, pivot intuitively and uncover hidden signals in real time for a fluid, context-aware experience. This not only accelerates investigations but makes advanced threat hunting accessible to every member of the SOC, regardless of experience level. Dynamic Threat Detection Agent – One of the hardest challenges in detection engineering is finding and fixing false negatives. The Dynamic Threat Detection Agent proactively hunts for false negatives and blind spots that traditional alerting might miss. When a critical incident happens, Copilot will kick off an automated hunt to uncover undetected threats—like unusual residual activity around a sensitive identity. This agent turns ‘probably fine’ into proven secure—hunting the quiet persistence that slips past alerts and closing the gap before it becomes tomorrow’s breach. Threat Intelligence (TI) Briefing Agent – Now native in the Defender portal. Generate tailored, AI‑authored threat briefings in minutes—synthesizing global intel with your environment’s context—without leaving the incident pane. Figure 1. The Threat Hunting Agent showing insights on an incident that contained a high risk binary To make the agents easily accessible and help security teams get started more quickly, we are excited to announce that Security Copilot will be available to all Microsoft 365 E5 customers. Rollout starts today for existing Security Copilot customers with Microsoft 365 E5 and will continue in the upcoming months for all Microsoft 365 E5 customers. Customers will receive 30-day advanced notification before activation. Learn more. Autonomous Defense at Platform Scale Threat actors are automating everything. Ransomware campaigns can encrypt an entire environment in under an hour. Adversaries evade detection and pivot across identities, endpoints, and cloud resources faster than human teams can triage alerts. Traditional SOC models—built on manual workflows and fragmented tools—simply can’t keep pace. Every second of delay gives attackers an advantage. Microsoft Defender now counters that speed by delivering autonomous defense at scale. Defender shifts security from reactive firefighting to proactive protection, embedding AI into the foundation of our protection solutions for instant detection, disruption, and containment—before threats escalate. In 2023, we introduced automatic attack disruption, which autonomously stops attacks in progress—like ransomware or business email compromise—with policy-bound actions that isolate endpoints, disable compromised accounts, and block malicious IPs at machine speed. Today, we’re taking the next step. New capabilities show how AI and agentic technology are transforming security to better protect customers: Unleash automatic attack disruption across your SIEM data: We are expanding the disruption capabilities of Microsoft Defender to some of the most critical data sources customer connect via Microsoft Sentinel including AWS, Proofpoint and Okta. This enables real-time detection and automatic containment of threats like phishing and identity compromise on top of your log data, fundamentally turning your SIEM into a threat protection solution. While these capabilities leverage the power of our platform, Defender is not a requirement for customers to realize this value in Microsoft Sentinel. Figure 2. Attack disruption initiated on an AWS attack Predictive shielding – This brand-new automatic attack disruption capability activates immediately after an attack is first contained. Our first of its kind capability combines graph insights, AI, and threat intelligence to predict potential attack paths for where the adversary might go next. It then applies just-in-time hardening techniques that proactively block the attacker from pivoting. Some of the hardening tactics that will automatically be applied by Microsoft Defender include disabling SafeBoot and enforcing Group Policy Objects, putting a hard stop to the attacker’s movements and ability to execute common techniques for compromise. Learn more about predictive shielding and other endpoint security news. Protect your low-code and pro-code AI agents Generative AI and agents are rapidly transforming how we work, but these powerful new tools also introduce new risks. And with the democratization of agent creation across pro-code, low-code, and no-code building platforms, building agents is now accessible to everyone, many without extensive developer or security knowledge. To help security teams better manage these risks we are excited to announce that we are extending the capabilities and experiences in Microsoft Defender to the protection of agents. From agent security posture management, to attack path analysis, and threat protection for Copilot Studio, Azure Foundry, and agents built and connected via the Microsoft Agent 365 SDK. Learn more about how Microsoft Defender can help protect your agents against threats like prompt injections and more. There is so much more innovation we are introducing in Microsoft Defender today, including expanded endpoint security coverage for legacy systems, improvements to how you can investigate identity-centric threats, and we are bringing cloud security posture management into the Defender portal. Check out the other Defender news blogs for more details. Join us in San Francisco, November 17–21, or online, November 18–20, for deep dives and practical labs to help you maximize your Microsoft Defender investments and to get more from the Microsoft capabilities you already use. Featured sessions: Microsoft Defender: Building the agentic SOC with guest Allie Mellen Blueprint for building the SOC of the future Empowering the SOC: Security Copilot and the rise of agentic defense Identity Under Siege: Modern ITDR from Microsoft AI vs AI: Protect email and collaboration tools with Microsoft Defender AI-powered defense for cloud workloads Endpoint security in the AI era: What's new in DefenderBetter together with Azure WAF + Microsoft Defender for Storage + Defender for Azure SQL Databases
Authored by: Fernanda_Vela , saikishor, Yura_Lee Reviewed by: YuriDiogenes, Mohit_Kumar, Amir_Dahan, eitanbremler , Kitt_Weatherman Introduction Often, customers ask why additional workload protection is needed when a web application firewall is already in place. Azure Web Application Firewall (WAF) serves as a critical control at the application edge, inspecting inbound HTTP/S traffic and blocking common web-based exploits before they reach backend services. However, modern attack paths are no longer limited to the web entry point. Attackers increasingly target components that bypass HTTP/S inspection altogether such as direct access to storage and SQL through SDKs, native integration tools, private endpoints, or compromised identities and third-party integrations. This is where Microsoft Defender for Cloud complements WAF. While WAF focuses on securing the application boundary, Defender for Cloud extends protection into the resource layer by providing Cloud-Native Application Protection Platform (CNAPP) capabilities, including security posture management and workload protection. Using resource-native signals, it helps identify misconfigurations and detect suspicious control-plane and data-plane activity that would otherwise remain invisible to perimeter controls. The Azure Networking Security blog post “Zero Trust with Azure Firewall, Azure DDoS Protection, and Azure WAF: A practical approach” highlights WAF’s role in inspecting inbound HTTP/S traffic, detecting malicious request patterns (such as OWASP Top 10 vulnerabilities), and reducing direct exposure of backend endpoints by enforcing a controlled application entry point. Building on that foundation, this blog focuses on a “better together” approach that combines WAF with Microsoft Defender for Cloud protecting storage and database. Through practical scenarios and posture insights, we will underline how these controls together: Reduces attack surface at the application entry point Continuously improves security posture through configuration and exposure analysis Detects and responds to threats targeting storage accounts and SQL databases beyond the web perimeter By the end of this post, you will understand how Defender for Cloud’s Storage and SQL protections extend the visibility provided by WAF, enabling protection not only at the edge, but also across the underlying data services. Together, these controls form a cohesive model that addresses both external attack vectors and internal or indirect access paths. Note: This is not a deep configuration guide for rule tuning, nor a replacement for official product documentation. It is intended to help architects and security teams align responsibilities and understand how these services reinforce each other. Architecture: The architecture below shows the traffic flow and where each service fits in the lab used in this blog to simulate the attacks. Azure Application Gateway with WAF is the internet-facing entry point, inspecting inbound HTTP/S traffic before it reaches the backend. Behind it, Azure Firewall provides both network- and application-layer inspection for inbound and outbound flows. In the backend subnet, multiple VMs host the workload. For our demonstration, we focus on a single host running: OWASP Juice Shop (port 3000), An upload API that writes to Azure Storage (port 8080) An API that connects to Azure SQL Database (port 5000). This setup allows us to simulate realistic attack paths originating both from the internet and from within the network. Figure 1: Architecture that shows resources with Application Gateway with WAF, Azure Firewall Premium and inbound traffic Note: The patterns in this blog apply to both Azure WAF platforms: Application Gateway WAF and Azure Front Door WAF. The lab uses Application Gateway WAF for the demonstration. Now, let’s head to the next section where we dive deep into these services to understand their capabilities with some attacks, alerts and insights. Azure Web Application Firewall at the Edge As we may have understood by now, Azure WAF is the first layer of protection, inspecting external web traffic for malicious patterns. Each incoming request is evaluated against its rulesets to either allow, block or log this traffic by using its managed and custom rulesets. Now, what are these rulesets? Azure WAF uses managed rule sets like the Default Rule Set (DRS) (version 2.2 as of this writing), which incorporate OWASP Top 10 protections and Microsoft threat intelligence to block common attacks (SQL injection, XSS, remote file inclusion, etc.) in real time. Additional managed sets include a Bot Protection rule set (to guard against malicious bots scraping content) and HTTP DDoS rule set (to detect Layer 7 DDoS patterns). Beyond the built-ins, you can define custom WAF rules for application-specific needs—blocking or allowing traffic based on attributes like geolocation, IP ranges, or specific URL paths. Now let’s talk about an example scenario. In our lab, Azure WAF is protecting multiple backend services on different paths and ports. When an external attacker tries to exploit the Juice Shop app with a crafted XSSattack, Azure WAF immediately detects the malicious pattern and blocks the request at the gateway as seen below. Figure 2: An XSS attack on the juiceshop website, immediately results in a 403 Forbidden as WAF catches this attack in the application layer. However, WAF’s inspection is inherently limited to traffic it can see, primarily, the HTTP/S flows it fronts. Let’s say our attacker changes tactics: instead of trying to force malicious code through the web interface, they obtain a stolen storage key or credentials through phishing and attempt to access the Azure Storage account directly via APIs. This request never goes through WAF, so WAF cannot assess or block it. In such a case, Microsoft Defender for Storage’s threat detection monitors for such suspicious activity, for example by raising an alert about the unusual direct access or flagging a malware file uploaded to a blob container. Likewise, if our attacker exploited a weakness in application code to run malicious SQL commands on the database (whether through potentially harmful application or a suspicious service account), Defender for SQL monitors for and alerts anomalous query patterns or suspicious logins. This illustrates why WAF and Defender for Cloud are complementary: WAF stops web attacks at the door, while Defender for Cloud watches for threats that get inside or come through alternate doors. Figure 3: Single-host lab architecture with Azure Application Gateway (WAF) and resource‑level protection Figure 3 illustrates the key distinction: WAF inspects and protects the application entry point, while Defender for Cloud provides visibility into the resources themselves. Together, they cover both the path into the application and the behavior within the environment—forming a complete protection model across layers. Because not all access to storage and databases may flow through the application gateway, you also need resource-level posture and threat detection to see and stop activity that never appears in WAF logs. Cloud Security Posture Management with Defender for Cloud With the edge covered, the next challenge is reducing risk that originates from misconfiguration and resource exposure. Most successful attacks originate from exposed services and misconfigurations rather than direct application-layer exploits. Microsoft Defender for Cloud’s storage and database protection provide security posture insights that help identify and prioritize these security gaps at the resource level. Defender for Cloud has visibility insights that capture the resources’ misconfigurations on the control and data plane via the Recommendations view in the Azure portal, as shown in the example below: Figure 4: Juice Shop’s storage account and SQL server recommendations Figure 4 is a list of recommendations organized by risk level for this particular environment. The security team should harden the “defendertestsai” storage asset by preventing shared access keys, and the “juiceshop” SQL database by provisioning an Entra administrator. Each recommendation will also provide guidance to remediate these findings. The “Data & AI Dashboard” in Defender for Cloud, with Defender CSPM, will also provide security posture insight into storage, database and AI resources by surfacing their risks, alerts and sensitive data discovery all in one dashboard. Figure 5: Juice Shop’s Sensitive data discovery and Data threat detection dashboard in Defender for Cloud’s “Data&AI section”. Under Data closer look, in Figure 5, you can see in this example, starting from the left, sensitive information found in scanned resources, level alerts for databases and storage resources based on severity, templatized queries from the Cloud Security Explorer, and a graph displaying all internet exposed data resources below. These powerful insights on data resources all come from Defender for Cloud, designed to help customers harden their environment by priority through visibility across their entire data ecosystem based on risk level. Figure 6: Juice Shop’s attack path “Internet exposed Azure VM with high severity vulnerabilities allows lateral movement to Critical Storage used by Azure AI Foundry”. Attack paths are potential avenues in which an attacker can infiltrate and compromise data. In Figure 6 above, we see insight into not only the storage account itself, but the context around it: an internet exposed storage account is connected to other assets like a virtual machine and a managed identity that has permissions to manipulate data. These Defender for Cloud security posture insights complement WAF and complete the defense-in-depth security approach: harden the data services so that even if an attacker reaches them the blast radius is smaller, and the likelihood of compromise is reduced. Defender for Cloud’s advanced threat protection Even in well-secured environments, attackers often interact directly with storage accounts or databases through identities, APIs, or trusted internal paths. Reducing exposure is critical but not sufficient. Detection is required once an attacker begins interacting with data Defender for Cloud’s advanced threat protection for Storage and SQL surfaces resource-level security alerts such as suspicious access patterns, anomalous queries, and malware detections—often with richer context than perimeter telemetry alone. Let’s use a malware alert for a storage account in the Defender portal as an example: Figure 7: Juice Shop’s storage account security alert “Malicious blob uploaded to storage account”. Malware scanning is a common requirement for teams that process user uploads or must meet security benchmarks. In this lab, Juice Shop allows users to upload files (for example, feedback attachments), and the upload API writes those files to Azure Blob Storage. Azure WAF inspects the HTTP request that delivers the upload headers, parameters, payload patterns and blocks web-layer attacks like XSS or SQLi. Scanning blob contents after they land is a different job, performed at the resource layer by Defender for Storage. With Defender for Storage malware scanning enabled, each uploaded blob is scanned; if the verdict is malware, Defender for Cloud raises an alert such as “Malicious blob uploaded to storage account” as shown in figure 7. Then, with Defender for Storage’s automated malware remediation, the malicious blog is set to soft-delete for quarantine and further analysis. SQL databases are high-value targets for data access, privilege escalation, and exploitation of vulnerable applications. Database protection in Defender for Cloud has the visibility to provide customers with control plane and data plane level insight to alert on suspicious activity such as anomalous logons, unusual client applications, and injection-like query patterns. For example, here’s a potential SQL injection alert for a database in the Defender portal: Figure 8: Juice Shop’s database security alert on a potential SQL injection. These alerts typically include investigation context such as the client application, client principal name, and the statement or pattern in question, along with severity to help you prioritize, as shown in Figure 8. From there, analysts can use recommended response actions (for example, to contain risky access paths or harden the database) to reduce the chance of repeat activity. In practice, Defender for Cloud threat detection gives SOC teams prioritized, resource-specific alerts with the context needed to investigate quickly and take action at the storage and database layers. Conclusion Azure Application Gateway with WAF is a necessary control to reduce application-layer risk at the edge. But defense in depth requires the assumption that some threats will reach or target data services directly. By layering Microsoft Defender for Storage and Microsoft Defender for SQL on top of Azure WAF, you add continuous posture insights to reduce preventable exposure, plus threat protection that detects suspicious activity at the resource layer. Operated together, these services provide stronger prevention, better detection coverage, and clearer response paths than single control alone.Monthly news - May 2026
Microsoft Defender Monthly news - May 2026 Edition This is our monthly "What's new" blog post, summarizing product updates and various new assets we released over the past month across our Defender products. In this edition, we are looking at all the goodness from April 2026. We are now including news related to Defender for Cloud in the Defender portal. For all other Defender for Cloud news, have a look at the dedicated Defender for Cloud Monthly News here. 🚀 New Virtual Ninja Show episode: The future of identity protection with Predictive Shielding Network-layer data protection with Microsoft Entra GSA and Purview DLP Data lake federation: hunt across external data without ingesting it Weekly Security News: We publish a short 1ish minute video every week with updates across our Microsoft Security stack. Subscribe to our YouTube channel, so you don't miss the next episode. Actionable threat insights CVE-2026-31431: Copy Fail vulnerability enables Linux root privilege escalation across cloud environments Email threat landscape: Q1 2026 trends and insights Cross‑tenant helpdesk impersonation to data exfiltration: A human-operated intrusion playbook Detection strategies across cloud and identities against infiltrating IT workers Dissecting Sapphire Sleet’s macOS intrusion from lure to compromise Microsoft Defender Blog post: Containing a domain compromise: How predictive shielding shut down lateral movement (Public Preview) You can now view the current status of automatic attack disruption and predictive shielding actions related to a specific incident. You view this data in the Activities tab of the incident page. Learn more We made several enhancements across the Advanced hunting experience, read this blog post for all the details. (Public Preview) The AIAgentsInfo table in advanced hunting now includes additional columns that provide deeper visibility into AI agents operating in your Microsoft 365 environment. These fields expand coverage beyond Copilot Studio to all agent types, including Microsoft Foundry, third-party marketplace, and custom line-of-business agents. (Generally Available) Built-in alert tuning rules are now generally available. Built-in alert tuning rules suppress alerts from common benign activity in Defender for Endpoint and Defender for Office 365 without affecting Automated Investigation and Response (AIR) investigations and email notifications. Microsoft Defender Experts for XDR customers can now see Defender Experts as a distinct entry in the Microsoft Defender portal navigation menu. This feature adds to the existing home page status card as in-portal experiences that provide consistent and predictable access to the service. Learn more Blog post: Simplifying AWS defense with Microsoft Sentinel UEBA Call to action: update automation by July 1, 2026 - Account Name is now consistently the UPN prefix for analytics rule alerts! Microsoft Sentinel is updating how the account entity's Account Name value is populated for analytics rule alerts when the full UPN is mapped into Account Name. This change improves consistency for downstream automation rules and Logic Apps playbooks. For more information, including before and after examples, read the blog article Update: Changing the Account Name Entity Mapping in Microsoft Sentinel. For all other Sentinel News, have a look at the "What's new in Microsoft Sentinel blog post - April edition" Microsoft Defender for Endpoint / Microsoft Defender Vulnerability Management (Public Preview) You can now view the current status of automatic attack disruption and predictive shielding actions related to a specific incident. You view this data in the Activities tab of the incident page. Learn more Microsoft Secure Score now includes the Ensure devices are updated to Secure Boot 2023 certificates and boot manager, which helps identify devices that haven't yet transitioned to the new Secure Boot 2023 certificates required ahead of the June 2026 expiration. To learn more about the recommendation, see Assess Secure Boot status with Microsoft Defender (blog). Microsoft Defender for Identity (Public Preview) Custom account correlation rules. Custom account correlation rules let you link accounts that belong to the same identity, such as privileged accounts with unique naming conventions. You can correlate accounts that don't share strong identifiers such as account ID, SID, object ID, or UPN by defining rules based on UPN prefix, UPN suffix, domain UPN, or employee ID. For more information, see Create custom account correlation rules. (Generally Available) The Automatic Windows event-auditing configuration for sensors v3.x is now generally available. Automatic Windows event-auditing streamlines deployment by automatically applying the required auditing settings to new sensors and correcting misconfigurations on existing ones.Monthly news - January 2026
Microsoft Defender Monthly news - January 2026 Edition This is our monthly "What's new" blog post, summarizing product updates and various new assets we released over the past month across our Defender products. In this edition, we are looking at all the goodness from December 2025. Defender for Cloud has its own Monthly News post, have a look at their blog space. 🚀 New Virtual Ninja Show episode: Advancements in Attack Disruption Vulnerability Remediation Agent in Microsoft Intune Microsoft Defender (Public Preview) The following advanced hunting schema tables are now available for preview: The CampaignInfo table contains contains information about email campaigns identified by Microsoft Defender for Office 365 The FileMaliciousContentInfo table contains information about files that were processed by Microsoft Defender for Office 365 in SharePoint Online, OneDrive, and Microsoft Teams General Availability of the Security Alert Triage Agent (previously named Phishing Triage Agent): this agent autonomously analyzes user‑reported phishing emails to determine whether they’re true threats or false positives, dramatically reducing manual triage workload. It continuously learns from analyst feedback and provides clear, natural‑language explanations for every verdict, giving SOC teams both speed and transparency. We're excited to share it is now generally available and, very soon, will expand to also triage cloud and identity alerts! Learn more on our docs. Public Preview of Dynamic Threat Detection Agent: Announced at Ignite, this always‑on agent hunts for unseen threats by continuously correlating telemetry and creating new, context‑aware detections on the fly—closing gaps traditional rules can’t see. We're excited to share it is now in Public Preview! Learn more on our docs. Public Preview of Threat Hunting Agent: Announced at Ignite, this agent gives every analyst the power to investigate like an expert by turning natural‑language questions into guided, real‑time hunts that surface hidden patterns, reveal meaningful pivots, and eliminate the need to write complex queries. We're excited to share it is now in Public Preview! Learn more on our docs. General Availability of the Threat Intelligence Briefing Agent: this agent delivers daily, tailored intelligence briefings directly in Microsoft Defender—automatically synthesizing Microsoft’s global threat insights with your organization’s context to surface prioritized risks, clear recommendations, and relevant assets so teams can shift from reactive research to proactive defense in minutes. We're excited to share it is now generally available! Learn more on our docs. (General Availability) The hunting graph in advanced hunting is now generally available. It also now has two new predefined threat scenarios that you can use to render your hunts as interactive graphs. (General Availability) Advanced hunting now supports custom functions that use tabular parameters. With tabular parameters, you can pass entire tables as inputs. This approach lets you build more modular, reusable, and expressive logic across your hunting queries. Learn more Note: The Phishing Triage Agent has since been expanded and is now called the Security Alert Triage Agent. Learn more at aka.ms/SATA Microsoft Defender for Endpoint (Public Preview) Triage collection: Use triage collection to prioritize incidents and hunt threats with the Sentinel Model Context Protocol (MCP) server. Microsoft Defender for Identity New ADWS LDAP search activity is now available in the 'IdentityQueryEvents' table in Advanced Hunting. This can provides visibility into directory queries performed through ADWS, helping customers track these operations and create custom detection based on this data. (Public Preview) New properties for 'sensorCandidate' resource type in Graph-API. Learn more here. Microsoft Defender for Cloud Apps Integration of Defender for Cloud Apps permissions with Microsoft Defender XDR Unified RBAC is now available worldwide. For more information, see Map Microsoft Defender for Cloud Apps permissions to the Microsoft Defender XDR Unified RBAC permissions. To activate the Defender for Cloud Apps workload, see Activate Microsoft Defender XDR Unified RBAC. (Public Preview) The Defender for Cloud Apps app governance unused app insights feature helps administrators identify and manage unused Microsoft 365-connected OAuth apps, enforce policy-based governance, and use advanced hunting queries for better security. This feature is now available for most commercial cloud customers. For more information, see Secure apps with app hygiene features.Microsoft Defender: New Advanced hunting enhancements
Co-author: Jeremy Tan As a security analyst who actively hunts for critical threats, one of the most frustrating things that can happen is hitting a limit mid-query or encounter an experience that doesn’t behave as expected. The resulting friction and time spent troubleshooting or navigating takes valuable focus away from the investigation itself. To address this, we’ve made several enhancements across the experience to ensure investigations can scale seamlessly so analysts can stay focused on finding and stopping threats without interruption. These updates are based on your feedback and our commitment to continually improve the experience for analysts and customers alike. Scaling Investigations with Expanded Limits We’ve made several enhancements across the experience to expand limits and better support large-scale investigations so analysts can query, explore, and act on more data with fewer constraints. Results limitation increase (Preview) We have heard your feedback on the need for larger data sets and are excited to announce that the results limitation in advanced hunting has been raised from 30,000 to 100,000 records. Now, queries returning up to 100,000 results will display all available data. If a query exceeds this threshold, results are truncated as before, but the increase allows for more comprehensive analysis and improved incident response. Records limitation picker (Preview) One common challenge in advanced hunting has been the risk of running queries that return overwhelming result sets, consuming excessive resources and potentially hitting system limits. The new records limitation picker addresses this by allowing you to explicitly set how many rows a query should return, directly from the editor toolbar. Choose from predefined limits: 1,000, 5,000, or 10,000, 30,000 and 100,000 rows. Select the maximum system limit (currently 100,000 records). Define a custom value as needed. The selected limit applies alongside any KQL-defined row limitations, with the lower value always taking precedence. Your choice persists across page refreshes, navigation, and browser restarts. By default, tenants start at the maximum row limit, but you can tailor your selection via page preferences. This enhancement greatly improves performance and prevents unexpected limitations, making hunting safer and more efficient. Partial results on size limit (GA) Previously, queries that exceeded the 64 mb results size limit would fail outright, forcing analysts to modify their queries and rerun them. With the latest update, partial results are now provided when the size limit is reached: Queries return the maximum records that fit within the 64 MB cap. A clear message bar indicates when results are partial due to size constraints. This allows you to act on available data immediately, without repeating query adjustments. This improvement speeds up investigations and provides valuable data even in scenarios where limits are reached. Enhanced UI for Faster, More Intuitive Investigations We’ve made significant enhancements to the user experience delivering a more streamlined interface that helps analysts move through incidents with greater clarity, act with confidence, and spend less time searching and more time responding. Hear from one of our customers: “The recent updates to the Defender Advanced Hunting experience have gone a long way toward decluttering the interface and lowering the barrier for analysts and engineers who were previously more comfortable working exclusively in Microsoft Sentinel in the Azure portal. By simplifying navigation, reducing unnecessary visual noise, and adding pinnable tabs, the XDR portal now feels more familiar. This usability improvement has helped shift long-standing Sentinel users toward the XDR experience without forcing a change in how teams think about their data or workflows.” -Matt McCullogh, Senior SIEM Engineer, Best Buy Query details side pane: enhanced visibility and troubleshooting (GA) Understanding query execution and troubleshooting errors has often required tedious trial and error. The new query execution details side pane surfaces rich, actionable metadata for every query—successful or failed. With this feature, you can: View execution time breakdowns, data sources, scopes, and resource utilization. Examine response characteristics and detailed error information. Navigate tabs such as overview, raw statistics, and errors for comprehensive diagnostics. Access the side pane easily after running a query, or even from error messages in failure scenarios. This transparency makes it far easier to investigate issues and optimize your hunting experience. Improved error-handling for Advanced hunting queries (GA) Advanced hunting now provides improved output messages, including clearer error messages that explain query failures and actionable suggestions for common issues. This update simplifies troubleshooting and helps reduce downtime with complex queries. Simpler Navigation, More Powerful Hunting Alongside these updates, the Advanced hunting UI has received several enhancements focused on usability and streamlined workflows. Users can now easily filter results with a single click, making data exploration more efficient and responsive and enhanced configuration of the schema tree now allows for collapsing or expanding all nodes with ease. Additionally, the page layout has been thoughtfully restructured, organizing components in a more intuitive manner for a modern, cohesive experience that makes advanced hunting both powerful and easy to use. Rename tabs (GA) Another notable usability enhancement is the ability for users to rename their working tabs within advanced hunting. This feature enables users to organize their work sessions more efficiently, allowing for clear identification of ongoing investigations and queries without requiring them to save their work as long-term functions or queries. By simply renaming tabs, users can quickly switch between tasks and keep their workspace well-structured, further improving workflow and productivity. Saving KQL functions to log analytics workspace (GA) In addition to the above enhancements, we are delighted to introduce the ability to save KQL functions directly from the advanced hunting page into your log analytics workspace. To utilize this feature: Pick a folder under shared functions → Sentinel workspace functions. Functions saved in this folder are available for use in workbooks, analytics rules, and for execution in advanced hunting. Note: functions saved here are not available in custom detection rules. This new capability empowers you to build reusable logic and streamline your security workflows across Microsoft Sentinel and advanced hunting. Conclusion These enhancements represent our continued commitment to supporting your security investigations with robust, flexible, and efficient tools. We look forward to your feedback and to bringing even more improvements in the future. Learn more about the new advanced hunting enhancements in our documentation.
