Announcing public preview: Uncovering hidden threats with the Dynamic Threat Detection Agent
Co-author: Amir Gharib At Ignite, we announced the Security Copilot Dynamic Threat Detection Agent in Microsoft Defender: an always on, adaptive backend agent that uncovers hidden threats across Defender and Microsoft Sentinel environments. Today we are excited to share that the customers who meet the prerequisites will now enter public preview of this agent. Running in the Defender backend, the agent delivers Copilot-sourced alerts directly into familiar workflows—complete with natural language explanations, mapped MITRE techniques, and tailored remediation steps. Why adaptive AI-driven detection changes the game Traditional rule-based and machine learning (ML) systems struggle to keep pace with ever-evolving threats. Attackers now leverage AI to evade detection, leaving organizations exposed. The Dynamic Threat Detection Agent addresses this through: Adaptive AI that finds what rules miss – GenAI-driven detection continuously investigates across Defender and Sentinel telemetry to uncover false negatives and blind spots, providing always-on protection with clear risk context and concrete next steps (see Figure 1 below). Reduce noise, increase confidence – The agent minimizes SOC noise and boosts analyst confidence, with customer-validated precision above 85% in recent months across thousands of alerts and 28 threat types (e.g., Initial Access, Privilege Escalation, Lateral Movement). Hyperscale TI + UEBA driven entity risk scoring – The agent fuses Threat Intelligence Tracking via Adaptive Networks (TITAN)’s hyperscale, ML-driven threat intelligence with UEBA risk signals to continuously score accounts, devices, and IPs. This combination of global TI, customer-specific context, and behavioral anomalies surfaces genuinely risky behaviors earlier while filtering noise and providing key context during the agent’s investigations. Always on, zero-touch—with customer control – Because the agent runs in the Defender backend, it automatically generates alerts into your existing XDR workflows with no tuning or onboarding required. During public preview it’s enabled by default for eligible customers, and starting in July it will be available for E5 customers through the Security Copilot inclusion. Once billing begins, customers can disable it at any time and manage usage through detailed consumption reporting. Deep integration across the Microsoft security ecosystem – The agent works with Security Copilot, Sentinel, and Defender, correlating native and third-party telemetry to surface missed behaviors and deliver richer context across your SOC workflows. Inside the Dynamic Threat Detection engine Under the hood, the Dynamic Threat Detection Agent runs a five-step investigation loop at machine scale—starting from signals you already care about, building a rich activity timeline, testing hypotheses, and closing detection gaps with explainable, actionable alerts. This loop executes across thousands of parallel investigations, delivering detections in near–real time for your SOC. Start with an incident – Running continuously in the Defender backend, the agent monitors for security activity you care about: incidents with a high priority score, critical assets, disruption signals, threat actor notifications, and more. Build a focused timeline – From that incident, it builds a unified activity timeline that stitches together alerts, events, UEBA anomalies, and threat intelligence. Iterative Q/A loop – Given the incident and its unified timeline, the agent automatically generates attack-specific hypotheses (e.g., “Was this account compromised via phishing from this IP?”) and runs its own chain of targeted questions over relevant entities and events. Without any manual prompts or intervention, the agent investigates its hypotheses, rules out alternate explanations, and autonomously converges on a single, well-supported triage decision with an explicit, transparent reasoning trace. Close detection gaps with explainable, actionable alerts – When evidence converges on a true positive, the agent automatically emits a dynamic alert—complete with title, description, severity, mapped MITRE techniques, and remediation steps—directly into your Defender workflows with Security Copilot as the detection source. Alongside the structured fields, the agent generates a natural language narrative that explains why the activity is risky, which entities and signals drove the decision, and how the attack unfolded, giving analysts a transparent window into its reasoning. Learn and improve continuously – Your grading feedback (TP/FP/BP) is leveraged to recalibrate seed points, refine table selection, tune hypothesis questions, and adjust thresholds so detection quality improves over time. This feedback continuously sharpens the agent’s ability to detect meaningful threats and reduce alert noise. Answering the questions security experts ask first Before adopting a new detection capability, security teams want more than features—they want clear answers on noise, effort, cost, explainability, and how it fits with their existing tools and compliance posture. The Dynamic Threat Detection Agent is built with those questions in mind, so from day one you know how it behaves in your SOC, how it’s governed, and what value it delivers. What’s the value? The agent uncovers hidden threats (i.e., false negative alerts), enriching investigations with context so analysts can resolve incidents faster and with greater confidence. Will this add noise? The agent is tuned for high precision—measured at 85+% over the past few months across thousands of alerts and numerous threat types (e.g., Initial Access, Privilege Escalation, Lateral Movement). How much effort is required? Zero setup—it runs in the Defender backend and delivers alerts into your current workflows. What about cost and control? Public Preview is free for Security Copilot customers. At General Availability (July 2026), the agent transitions to the Security Copilot SCU-based model; you’ll have consumption reporting and the ability to disable the agent if desired. Microsoft Security Copilot is now included for all eligible Microsoft 365 E5 customers. Learn more. Is it explainable? Every alert includes a custom description, mapped MITRE techniques, and tailored remediation actions. Alongside the structured fields, it generates a natural language narrative that explains why the activity is risky, which entities and signals drove the decision, and how the attack unfolded, giving analysts a transparent window into the agent’s reasoning Does it respect data residency? The service runs region local, ensuring that customer data and required telemetry stay inside the designated geographic boundary. How does it fit with Sentinel and Security Copilot? The agent uses Sentinel to correlate third-party and native telemetry, and runs as part of the Security Copilot platform—surfacing its alerts as Copilot-sourced detections in Defender. How fast and at what scale? The agent is built for massive scale with Azure Synapse, capable of running thousands of parallel investigations and delivering detections in near–real time for your SOC. The future of dynamic threat detection in your SOC The Dynamic Threat Detection Agent is a milestone in adaptive security—bringing GenAI to detection at scale, integrated across Defender and Sentinel, and delivered through Security Copilot. We’re just getting started: expect continued enhancements in coverage, contextual explainability, and integration with your SOC workflows. Public Preview starts now. The Dynamic Threat Detection Agent is available as a free Public Preview for Security Copilot customers. General Availability (GA) planned for late 2026, the agent will transition to the Security Copilot SCU-based consumption model. Microsoft Security Copilot is now included for all eligible Microsoft 365 E5 customers, and this agent will be included as part of that entitlement. Learn more and get started Check out our resources to learn more about the new Security Copilot Dynamic Threat Detection Agent: Check out Microsoft Ignite announcement and demo Read the documentation on the new agent experience hereUnlocking Real-World Security: Defending against Crypto mining attacks
In this anonymized case study, we explore a crypto mining attack that starts with a password spray, escalates through privilege abuse, and culminates in cloud resource exploitation. This scenario demonstrates how Defender for Cloud, in collaboration with other Microsoft Security solutions, not only detects and responds to threats but also disrupts attacks in real time to prevent further damage and lateral movement.Hyperscale ML threat intelligence for early detection & disruption
Co-author: Amir Gharib In today's rapidly evolving cybersecurity landscape, the ability to swiftly identify and mitigate threats is more critical than ever. Attackers are increasingly well-resourced, enabling them to keep adding new components to their toolkits that keep their infrastructure fresh and hard to detect. Traditional labeling methods used to identify and block malicious infrastructure are struggling to keep up. At Microsoft, we recognize the pressing need for innovative solutions that not only keep pace with these threats but stay ahead of them. This past Ignite, we announced Threat Intelligence Tracking via Dynamic Networks (TITAN)—a groundbreaking approach that uses the power of machine learning to transform threat intelligence and attack disruption by automatically neutralizing malicious activity at scale. By leveraging real-time ML-driven analytics, TITAN uncovers previously hidden threat actor infrastructure, enabling the disruption capabilities built into our unified security operations platform to detect and stop attacks significantly earlier in the attack chain (Figure 1). The power of machine-scale threat intelligence TITAN represents a new wave of innovation built on Microsoft threat intelligence capabilities, introducing a real-time, adaptive threat intelligence (TI) graph that integrates first and third-party telemetry from the unified security operations platform, Microsoft Defender for Threat Intelligence, Microsoft Defender for Experts, and customer feedback. This graph employs guilt-by-association techniques to propagate known TI labels to unknown neighboring entities (e.g., IP, file, email) at machine scale. By analyzing relationships between entities, TITAN can identify attacker infrastructure before they are leveraged in attacks, providing an invaluable window of opportunity to prevent harm. Figure 1. Architectural overview of TITAN, comprising four key steps: (1) constructing a graph using telemetry from 1 st and 3 rd party detectors in the Unified Security Operations Platform, (2) integrating known threat intelligence from across Microsoft, (3) applying reputation propagation algorithms to classify previously unknown entities as either benign or malicious, and (4) updating the reputation score for each entity in the graph. By leveraging guilt-by-association methods, TITAN can swiftly identify hidden threat actor infrastructure through cross-organizational associations with known malicious entities within the TI graph. Specifically, we employ a semi-supervised label propagation technique that iteratively assigns reputation scores to nodes based on their neighbors’ scores, refining the graph’s score distribution until convergence. These high-confidence entity reputation scores empower the unified security operations platform to implement proactive containment and remediation actions via attack disruption. A key advantage of our constantly evolving threat intelligence is that we can provide clear and explainable reputation scores for each entity by examining the neighboring entities that contribute to the overall score. Preventing attacks before they happen Consider a scenario where TITAN detects unusual activity from a seemingly benign IP address that has connections to known malicious domains. Traditional systems might not flag this IP until after malicious activity is confirmed. However, TITAN's guilt-by-association techniques elevate the reputation score of the IP address, immediately triggering detection and disruption rules that block the threat before any damage occurs. With an impressive average macro-F1 score of 0.89 and a precision-recall AUC of 0.94, TITAN identifies millions of high-risk entities each week, enabling a 6x increase in non-file threat intelligence. Since its deployment, TITAN has reduced the time to disrupt by a factor of 1.9x while maintaining 99% precision, as confirmed by customer feedback and thorough manual evaluation by security experts—ultimately saving customers from costly security breaches. Dynamic threat intelligence graph construction At the heart of TITAN is a dynamic, time-evolving threat intelligence graph that captures complex relationships between millions of interlinked entities, alerts, and incidents. By combining telemetry across both 1 st and 3 rd party sources in the unified security operations platform, TITAN is uniquely positioned for comprehensive view of the threat landscape, essential for early detection and disruption. Key features include: Real-time updates – In cybersecurity, speed is critical. TITAN operates in real-time, with graph creation and reputation propagation algorithms running every hour. This frequency ensures that security teams receive fresh and active threat intelligence, enabling swift and effective responses to emerging threats. The ability to act quickly can mean the difference between thwarting an attack and being breached. Infusing security domain knowledge via edge weights – Edges in the TI graph carry weights that signify the strength or relevance of the relationships between entities. We introduce edge weight decay functions that automatically reduce edge weights based on the time elapsed since the edge was formed. This ensures that newer and more relevant relationships have a greater impact on reputation assessments, aligning the dynamic graph with the real-time nature of security incidents. Pruning outdated nodes and edges – To maintain the relevance and efficiency of the TI graph, we implement pruning mechanisms that remove nodes and edges when their weights fall below certain thresholds. This approach keeps the graph focused on the most current and meaningful connections, ensuring optimal performance. Evolving cybersecurity defense with TI TITAN represents a monumental step forward in the mission to protect organizations from cyber threats. By infusing the power of AI with advanced threat intelligence, we are equipping security teams with the tools they need to stay ahead of the attackers. This is only possible with a unified platform that consolidates threat intelligence across 1 st and 3 rd party workloads and products, organizations benefit not only from streamlining their security operations but also gain deeper insights into potential threats and vulnerabilities. TITAN is just one of the many examples of how powerful bringing together the full capabilities of an industry-leading cloud-native security information and event management (SIEM), comprehensive extended detection and response (XDR), and generative AI built specifically for cybersecurity. Integrating all of this data, advanced analysis, threat intel and automation enables an entirely new era of defense for security teams and we’re so energized by the potential. TITAN is just the start – look forward to new capabilities announced in the coming months. Learn More Check out our resources to learn more about our new approach to AI-driven threat intelligence, and our recent security announcements: See TITAN in action in the session delivered at Ignite Read the full paper on the TITAN architecture Read the Copilot for Security Guided Response paper & blog Read the unified security operations platform GA announcementData lake tier Ingestion for Microsoft Defender Advanced Hunting Tables is Now Generally Available
Today, we’re excited to announce the general availability (GA) of data lake tier ingestion for Microsoft XDR Advanced Hunting tables into Microsoft Sentinel data lake. Security teams continue to generate unprecedented volumes of high‑fidelity telemetry across endpoints, identities, cloud apps, and email. While this data is essential for detection, investigation, and threat hunting, it also creates new challenges around scale, cost, and long‑term retention. With this release, users can now ingest Advanced Hunting data from: Microsoft Defender for Endpoint (MDE) Microsoft Defender for Office 365 (MDO) Microsoft Defender for Cloud Apps (MDA) directly into Sentinel data lake, without requiring ingestion into the Microsoft Sentinel Analytics tier. Support for Microsoft Defender for Identity (MDI) Advanced Hunting tables will follow in the near future. Supported Tables This release enables data lake tier ingestion for Advanced Hunting data from: Defender for Endpoint (MDE) – DeviceInfo, DeviceNetworkInfo, DeviceProcessEvents, DeviceNetworkEvents, DeviceFileEvents, DeviceRegistryEvents, DeviceLogonEvents, DeviceImageLoadEvents, DeviceEvents, DeviceFileCertificateInfo Defender for Office 365 (MDO) – EmailAttachmentInfo, EmailEvents, EmailPostDeliveryEvents, EmailUrlInfo, UrlClickEvents Defender for Cloud Apps (MDA) – CloudAppEvents Each source is ingested natively into Sentinel data lake, aligning with Microsoft’s broader lake‑centric security data strategy. As mentioned above, Microsoft Defender for Identity will be available in the near future. What’s New with data lake Tier Ingestion Until now, Advanced Hunting data was primarily optimized for near‑real‑time security operations and analytics. As users extend their detection strategies to include longer retention, retrospective analysis, AI‑driven investigations, and cross‑domain correlation, the need for a lake‑first architecture becomes critical. With data lake tier ingestion, Sentinel data lake becomes a must-have destination for XDR insights, enabling users to: Store high‑volume Defender Advanced Hunting data efficiently at scale while reducing operation overhead Extend security analytics and data beyond traditional analytics lifespans for investigation, compliance, and threat research with up to 12 years of retention Query data using KQL‑based experiences across unified datasets with the KQL explorer, KQL Jobs, and Notebook Jobs Integrate data with AI-driven tooling via MCP Server for quick and interactive insights into the environment Visualize threat landscapes and relational mappings while threat hunting with custom Sentinel graphs Decouple storage and retention decisions from real‑time SIEM operations while building a more flexible and futureproof Sentinel architecture Enabling Sentinel data lake Tier Ingestion for Advanced Hunting Tables The ingestion pipeline for sending Defender Advanced Hunting data to Sentinel data lake leverages existing infrastructure and UI experiences. To enable Advanced Hunting tables for Sentinel data lake ingestion: Within the Defender Portal, expand the Microsoft Sentinel section in the left navigation. Go to Configuration > Tables. Find any of the listed tables from above and select one. Within the side menu that opens, select Data Retention Settings. Once the options open, select the button next to ‘Data lake tier’ to set the table to ingest directly into Sentinel data lake. Set the desired total retention for the data. Click save. This configuration will allow Defender data to reside within each Advanced Hunting table for 30 days while remaining accessible via custom detections and queries, while a copy of the logs is sent to Sentinel data lake for usage with custom graphs, MCP server, and benefit from the option of retention up to 12 years. Why data lake Tier Ingestion Matters Built for Scale and Cost Efficiency Advanced Hunting data is rich—and voluminous. Sentinel data lake enables users to store this data using a lake‑optimized model, designed for high‑volume ingestion and long‑term analytical workloads while making it easy to manage table tiers and usage. A Foundation for Advanced Analytics With Defender data co‑located alongside other security and cloud signals, users can unlock: Cross‑domain investigations across endpoint, identity, cloud, and email Retrospective hunting without re‑ingestion AI‑assisted analytics and large‑scale pattern detection Flexible Architecture for Modern Security Teams Data lake tier ingestion supports a layered security architecture, where: Workspaces remain optimized for real‑time detection and SOC workflows The data lake serves as the cost-effective and durable system for security telemetry Users can choose the right level of ingestion depending on operational needs, without duplicating data paths or cost. Designed to Work with Existing Sentinel and XDR Experiences This GA release builds on Microsoft Sentinel’s ongoing investment in unified data configuration and management: Native integration with Microsoft Defender XDR Advanced Hunting schemas Alignment with existing Sentinel data lake query and exploration experiences Consistent management alongside other first‑party and third‑party data sources Consistent experiences within the Defender Portal No changes are required to existing Defender deployments to begin using data lake tier ingestion. Get started To learn more about Microsoft Sentinel Data Lake and managing Defender XDR data within Sentinel, visit the Microsoft Sentinel documentation and explore how lake‑based analytics can complement your existing security operations. We look forward to seeing how users use this capability to explore new detection strategies, perform deeper investigations, and build long‑term security habits.Security Copilot Skilling Series
Security Copilot joins forces with your favorite Microsoft Security products in a skilling series miles above the rest. The Security Copilot Skilling Series is your opportunity to strengthen your security posture through threat detection, incident response, and leveraging AI for security automation. These technical skilling sessions are delivered live by experts from our product engineering teams. Come ready to learn, engage with your peers, ask questions, and provide feedback. Upcoming sessions are noted below and will be available on-demand on the Microsoft Security Community YouTube channel. Coming Up February 5 | Identity Risk Management in Microsoft Entra Speaker: Marilee Turscak Identity teams face a constant stream of risky user signals, and determining which threats require action can be time‑consuming. This webinar explores the Identity Risk Management Agent in Microsoft Entra, powered by Security Copilot, and how it continuously monitors risky identities, analyzes correlated sign‑in and behavior signals, and explains why a user is considered risky. Attendees will see how the agent provides guided remediation recommendations—such as password resets or risk dismissal—at scale and supports natural‑language interaction for faster investigations. The session also covers how the agent learns from administrator instructions to apply consistent, policy‑aligned responses over time. February 19 | Agents That Actually Work: From an MVP Speaker: Ugur Koc, Microsoft MVP Microsoft MVP Ugur Koc will share a real-world workflow for building agents in Security Copilot, showing how to move from an initial idea to a consistently performing agent. The session highlights how to iterate on objectives, tighten instructions, select the right tools, and diagnose where agents break or drift from expected behavior. Attendees will see practical testing and validation techniques, including how to review agent decisions and fine-tune based on evidence rather than intuition to help determine whether an agent is production ready. March 5 | Conditional Access Optimization Agent: What It Is & Why It Matters Get a clear, practical look at the Conditional Access Optimization Agent—how it automates policy upkeep, simplifies operations, and uses new post‑Ignite updates like Agent Identity and dashboards to deliver smarter, standards‑aligned recommendations. Now On-Demand January 28 | Security Copilot in Purview Technical Deep Dive Speakers: Patrick David, Thao Phan, Alexandra Roland Discover how AI-powered alert triage agents for Data Loss Prevention (DLP) and Insider Risk Management (IRM) are transforming incident response and compliance workflows. Explore new Data Security Posture Management (DSPM) capabilities that deliver deeper insights and automation to strengthen your security posture. This session will showcase real-world scenarios and actionable strategies to help you protect sensitive data and simplify compliance. January 22 | Security Copilot Skilling Series | Building Custom Agents: Unlocking Context, Automation, and Scale Speakers: Innocent Wafula, Sean Wesonga, and Sebuh Haileleul Microsoft Security Copilot already features a robust ecosystem of first-party and partner-built agents, but some scenarios require solutions tailored to your organization’s specific needs and context. In this session, you'll learn how the Security Copilot agent builder platform and MCP servers empower you to create tailored agents that provide context-aware reasoning and enterprise-scale solutions for your unique scenarios. December 18 | What's New in Security Copilot for Defender Speaker: Doug Helton Discover the latest innovations in Microsoft Security Copilot embedded in Defender that are transforming how organizations detect, investigate, and respond to threats. This session will showcase powerful new capabilities—like AI-driven incident response, contextual insights, and automated workflows—that help security teams stop attacks faster and simplify operations. Why Attend: Stay Ahead of Threats: Learn how cutting-edge AI features accelerate detection and remediation. Boost Efficiency: See how automation reduces manual effort and improves SOC productivity. Get Expert Insights: Hear directly from product leaders and explore real-world use cases. Don’t miss this opportunity to future-proof your security strategy and unlock the full potential of Security Copilot in Defender! December 4 | Discussion of Ignite Announcements Speakers: Zineb Takafi, Mike Danoski and Oluchi Chukwunwere, Priyanka Tyagi, Diana Vicezar, Thao Phan, Alex Roland, and Doug Helton Ignite 2025 is all about driving impact in the era of AI—and security is at the center of it. In this session, we’ll unpack the biggest Security Copilot announcements from Ignite on agents and discuss how Copilot capabilities across Intune, Entra, Purview, and Defender deliver end-to-end protection. November 13 | Microsoft Entra AI: Unlocking Identity Intelligence with Security Copilot Skills and Agents Speakers: Mamta Kumar, Sr. Product Manager; Margaret Garcia Fani, Sr. Product Manager This session will demonstrate how Security Copilot in Microsoft Entra transforms identity security by introducing intelligent, autonomous capabilities that streamline operations and elevate protection. Customers will discover how to leverage AI-driven tools to optimize conditional access, automate access reviews, and proactively manage identity and application risks - empowering them into a more secure, and efficient digital future. October 30 | What's New in Copilot in Microsoft Intune Speaker: Amit Ghodke, Principal PM Architect, CxE CAT MEM Join us to learn about the latest Security Copilot capabilities in Microsoft Intune. We will discuss what's new and how you can supercharge your endpoint management experience with the new AI capabilities in Intune. October 16 | What’s New in Copilot in Microsoft Purview Speaker: Patrick David, Principal Product Manager, CxE CAT Compliance Join us for an insider’s look at the latest innovations in Microsoft Purview —where alert triage agents for DLP and IRM are transforming how we respond to sensitive data risks and improve investigation depth and speed. We’ll also dive into powerful new capabilities in Data Security Posture Management (DSPM) with Security Copilot, designed to supercharge your security insights and automation. Whether you're driving compliance or defending data, this session will give you the edge. October 9 | When to Use Logic Apps vs. Security Copilot Agents Speaker: Shiv Patel, Sr. Product Manager, Security Copilot Explore how to scale automation in security operations by comparing the use cases and capabilities of Logic Apps and Security Copilot Agents. This webinar highlights when to leverage Logic Apps for orchestrated workflows and when Security Copilot Agents offer more adaptive, AI-driven responses to complex security scenarios. All sessions will be published to the Microsoft Security Community YouTube channel - Security Copilot Skilling Series Playlist __________________________________________________________________________________________________________________________________________________________________ Looking for more? Keep up on the latest information on the Security Copilot Blog. Join the Microsoft Security Community mailing list to stay up to date on the latest product news and events. Engage with your peers one of our Microsoft Security discussion spaces.Automating Microsoft Sentinel: Part 2: Automate the mundane away
Welcome to the second entry of our blog series on automating Microsoft Sentinel. In this series, we’re showing you how to automate various aspects of Microsoft Sentinel, from simple automation of Sentinel Alerts and Incidents to more complicated response scenarios with multiple moving parts. So far, we’ve covered Part 1: Introduction to Automating Microsoft Sentinel where we talked about why you would want to automate as well as an overview of the different types of automation you can do in Sentinel. Here is a preview of what you can expect in the upcoming posts [we’ll be updating this post with links to new posts as they happen]: Part 1: Introduction to Automating Microsoft Sentinel Part 2: Automation Rules [You are here] – Automate the mundane away Part 3: Playbooks 1 – Playbooks Part I – Fundamentals Part 4: Playbooks 2 – Playbooks Part II – Diving Deeper Part 5: Azure Functions / Custom Code Part 6: Capstone Project (Art of the Possible) – Putting it all together Part 2: Automation Rules – Automate the mundane away Automation rules can be used to automate Sentinel itself. For example, let’s say there is a group of machines that have been classified as business critical and if there is an alert related to those machines, then the incident needs to be assigned to a Tier 3 response team and the severity of the alert needs to be raised to at least “high”. Using an automation rule, you can take one analytic rule, apply it to the entire enterprise, but then have an automation rule that only applies to those business-critical systems to make those changes. That way only the items that need that immediate escalation receive it, quickly and efficiently. Automation Rules In Depth So, now that we know what Automation Rules are, let’s dive in to them a bit deeper to better understand how to configure them and how they work. Creating Automation Rules There are three main places where we can create an Automation Rule: 1) Navigating to Automation under the left menu 2) In an existing Incident via the “Actions” button 3) When writing an Analytic Rule, under the “Automated response” tab The process for each is generally the same, except for the Incident route and we’ll break that down more in a bit. When we create an Automation Rule, we need to give the rule a name. It should be descriptive and indicative of what the rule is going to do and what conditions it applies to. For example, a rule that automatically resolves an incident based on a known false positive condition on a server named SRV02021 could be titled “Automatically Close Incident When Affected Machine is SRV02021” but really it’s up to you to decide what you want to name your rules. Trigger The next thing we need to define for our Automation Rule is the Trigger. Triggers are what cause the automation rule to begin running. They can fire when an incident is created or updated, or when an alert is created. Of the two options (incident based or alert based), it’s preferred to use incident triggers as they’re potentially the aggregation of multiple alerts and the odds are that you’re going to want to take the same automation steps for all of the alerts since they’re all related. It’s better to reserve alert-based triggers for scenarios where an analytic rule is firing an alert, but is set to not create an incident. Conditions Conditions are, well, the conditions to which this rule applies. There are two conditions that are always present: The Incident provider and the Analytic rule name. You can choose multiple criterion and steps. For example, you could have it apply to all incident providers and all rules (as shown in the picture above) or only a specific provider and all rules, or not apply to a particular provider, etc. etc. You can also add additional Conditions that will either include or exclude the rule from running. When you create a new condition, you can build it out by multiple properties ranging from information about the Incident all the way to information about the Entities that are tagged in the incident Remember our earlier Automation Rule title where we said this was a false positive about a server name SRV02021? This is where we make the rule match that title by setting the Condition to only fire this automation if the Entity has a host name of “SRV2021” By combining AND and OR group clauses with the built in conditional filters, you can make the rule as specific as you need it to be. You might be thinking to yourself that it seems like while there is a lot of power in creating these conditions, it might be a bit onerous to create them for each condition. Recall earlier where I said the process for the three ways of creating Automation Rules was generally the same except using the Incident Action route? Well, that route will pre-fill variables for that selected instance. For example, for the image below, the rule automatically took the rule name, the rules it applies to as well as the entities that were mapped in the incident. You can add, remove, or modify any of the variables that the process auto-maps. NOTE: In the new Unified Security Operations Platform (Defender XDR + Sentinel) that has some new best practice guidance: If you've created an automation using "Title" use "Analytic rule name" instead. The Title value could change with Defender's Correlation engine. The option for "incident provider" has been removed and replaced by "Alert product names" to filter based on the alert provider. Actions Now that we’ve tuned our Automation Rule to only fire for the situations we want, we can now set up what actions we want the rule to execute. Clicking the “Actions” drop down list will show you the options you can choose When you select an option, the user interface will change to map to your selected option. For example, if I choose to change the status of the Incident, the UX will update to show me a drop down menu with options about which status I would like to set. If I choose other options (Run playbook, change severity, assign owner, add tags, add task) the UX will change to reflect my option. You can assign multiple actions within one Automation Rule by clicking the “Add action” button and selecting the next action you want the system to take. For example, you might want to assign an Incident to a particular user or group, change its severity to “High” and then set the status to Active. Notably, when you create an Automation rule from an Incident, Sentinel automatically sets a default action to Change Status. It sets the automation up to set the Status to “Closed” and a “Benign Positive – Suspicious by expected”. This default action can be deleted and you can then set up your own action. In a future episode of this blog we’re going to be talking about Playbooks in detail, but for now just know that this is the place where you can assign a Playbook to your Automation Rules. There is one other option in the Actions menu that I wanted to specifically talk about in this blog post though: Incident Tasks Incident Tasks Like most cybersecurity teams, you probably have a run book of the different tasks or steps that your analysts and responders should take for different situations. By using Incident Tasks, you can now embed those runbook steps directly in the Incident. Incident tasks can be as lightweight or as detailed as you need them to be and can include rich formatting, links to external content, images, etc. When an incident with Tasks is generated, the SOC team will see these tasks attached as part of the Incident and can then take the defined actions and check off that they’ve been completed. Rule Lifetime and Order There is one last section of Automation rules that we need to define before we can start automating the mundane away: when should the rule expire and in what order should the rule run compared to other rules. When you create a rule in the standalone automation UX, the default is for the rule to expire at an indefinite date and time in the future, e.g. forever. You can change the expiration date and time to any date and time in the future. If you are creating the automation rule from an Incident, Sentinel will automatically assume that this rule should have an expiration date and time and sets it automatically to 24 hours in the future. Just as with the default action when created from an incident, you can change the date and time of expiration to any datetime in the future, or set it to “Indefinite” by deleting the date. Conclusion In this blog post, we talked about Automation Rules in Sentinel and how you can use them to automate mundane tasks in Sentinel as well as leverage them to help your SOC analysts be more effective and consistent in their day-to-day with capabilities like Incident Tasks. Stay tuned for more updates and tips on automating Microsoft Sentinel!Microsoft Purview Data Security Investigations is now generally available
Every data security investigation starts with the same question: What data security risks are buried in this data? Exposed credentials in thousands of files across a data estate. Evidence of fraud hidden in vendor communications. Sensitive documents accidentally shared to a large group. Finding these risks manually — reviewing content file by file, message by message — is no longer viable when organizations are managing 220 zettabytes of data[1] and facing over 12,000 confirmed breaches annually[2]. That's why we built Microsoft Purview Data Security Investigations, now generally available. Microsoft Purview Data Security Investigations enables data security teams to identify investigation-relevant data, investigate that data with AI-powered deep content analysis, and mitigate risk — all within one unified solution. Teams can quickly analyze data at scale to surface sensitive data and security risks, then collaborate securely to address them. By streamlining complex, time‑consuming investigative workflows, admins can resolve investigations in hours instead of weeks or months. Proactive and reactive investigation scenarios Organizations are using Data Security Investigations to tackle diverse data security challenges — from reactive incident response to proactive risk assessment. Some of our top use cases from preview include: Data breach and leak: Understand severity, sensitivity, and significance of data that has been leaked or breached, including risks buried in impacted data, to take action and mitigate its impact to the organization. Credentials exposure: Proactively scan thousands of SharePoint sites to identify files containing credentials like passwords, which can give a threat actor prolonged access to an organization's environment. Internal fraud and bribery: Uncover suspicious communications tied to vendor payments or client interactions, uncovering hard-to-find patterns in large volumes of emails and messages. Sensitive data exposure in Teams: Determine who accessed classified documents after accidental sharing — and whether that data was further distributed. Inappropriate content investigations: Quickly find what was posted, where, and by whom, even when teams only know a timeframe or channel name. Investigations that once took weeks — or weren’t possible at all — can now be completed in hours. By eliminating manual effort and surfacing hidden risks across sprawling data estates, Data Security Investigations empowers teams to investigate more efficiently and confidently, making deep, scalable investigations a reality. What Microsoft Purview Data Security Investigations does – and what’s new Since launching public preview, we've listened closely to customer feedback and made significant enhancements to help teams investigate faster, mitigate more effectively, and manage costs with confidence. Data Security Investigations addresses three critical stages of an investigation: Identify impacted data Data Security admins can efficiently identify relevant data by searching their Microsoft 365 data estate to locate emails, Teams messages, Copilot prompts and responses, and documents. Investigators can also launch pre-scoped investigations from a Microsoft Defender XDR incident or a Microsoft Purview Insider Risk Management case. We’ve recently added a new integration that allows admins to launch a Data Security Investigation from Microsoft Purview Data Security Posture Management as well. This capability can help a data security admin investigate an objective, such as preventing data exfiltration. Investigate using deep content analysis Once the investigation is scoped, the solution's generative AI capabilities allow admins to gain deeper insights into the data, analyzing across 95+ languages to uncover critical sensitive data and security risks. Teams can quickly answer three questions: What data security risks exist within the data? Why do they matter? And what actions can be taken to mitigate them? To help answer these questions, two new investigative capabilities, AI search and AI context input, as well as enhancements to existing features were added in November. Data Security Investigations help admins scale their impact and accelerate investigations with the following features: AI search: Using a new AI-powered natural language search experience, admins can find key risks using keywords, metadata, and semantic embeddings — making it easier to locate investigation-relevant content across large data estates. Categorization: By automatically classifying investigation data into meaningful categories, admins can quickly understand incident severity, what types of content is at risk, and trends within an investigation. Vector search: Using semantic search, admins can find contextually related content — even when exact keywords don't match. Risk examination: Using deep content analysis, admins can examine content for sensitive data and security risks, providing a risk score, recommended mitigation steps, and AI-generated rationale for each analyzed asset. AI context input: Admins can now add investigation-specific context before analysis, resulting in more efficient, higher-quality insights tailored to the specific incident. AI search in action, finding credentials present in the dataset being investigated. Mitigate identified risks Investigators can use Data Security Investigations to securely collaborate with partner teams to mitigate identified risks, simplifying tasks that have traditionally been time consuming and complex. In September, we launched an integration with the Microsoft Sentinel graph, the data risk graph, allowing admins to visualize correlations between investigation data, users, and their activities. This automatically combines unified audit logs, Entra audit logs, and threat intelligence, which would otherwise need to be manually correlated, saving time, providing critical context, and allowing investigators to understand all nodes in their investigation. At the start of January 2026, we launched a new mitigation action, purge, that helps admins quickly and efficiently delete sensitive or overshared content directly within the investigation workflow in the product interface. This reduces exposure immediately and keeps incidents from escalating or recurring. Built-in cost management tools To help customers predict and manage costs associated with using Data Security Investigations, we recently released a lightweight cost estimator and usage dashboard. The in-product cost estimator is now available to help analysts model and forecast both storage and compute unit costs based on specific use cases, enabling more accurate budget planning. Additionally, the usage dashboard provides granular breakdowns of billed storage and compute unit usage, empowering data security admins to identify cost-saving opportunities and optimize resource allocation. For detailed guidance on managing costs, see https://aka.ms/DSIcostmanagementtips. Refined business model for general availability These cost management tools are designed to support our updated business model, which offers greater flexibility and transparency. Customers need the freedom to scale investigations without overcommitting resources. To better align with how customers investigate data risk at scale, we refined the Data Security Investigations business model as part of general availability. The product now uses two consumptive meters: Data Security Investigations Storage Meter – For storing investigation-related data, charged by GB Data Security Investigations Compute Meter – For the computational capacity required to complete AI-powered data analysis and actions, charged by Compute Units (CUs) Monthly charges are determined by the amount of data stored and the number of CUs consumed per hour. This pay-as-you-go model ensures customers only pay for what they need when they need it, providing the flexibility, scalability, and cost efficiency needed for both urgent incident response and proactive data security hygiene assessments. Find more information on pricing at aka.ms/purviewpricing. Get started today As data security threats evolve, so must the way we investigate them. Microsoft Purview Data Security Investigations is now generally available, giving organizations a modern, AI-powered approach to uncovering and mitigating risk — without the complexity of disconnected tools or manual workflows. Whether investigating an active breach or proactively hunting for hidden risks, Data Security Investigations gives data security teams the speed and precision needed to act decisively in today's threat landscape. Join for a live Ask Me Anything with the people behind the product on Thursday February 5th at 10am PST, more details here: aka.ms/PurviewDSIAMA2 Learn more about Data Security Investigations at aka.ms/DSIdocs View pricing details at aka.ms/purviewpricing Try Data Security Investigations today! Visit the product https://purview.microsoft.com/dsi and find setup instructions at aka.ms/DSIsetup [1] Worldwide IDC Global DataSphere Forecast, 2025–2029 [2] 2025-dbir-data-breach-investigations-report.pdfMonthly 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 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 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.
