Microsoft Sentinel
731 TopicsMicrosoft Sentinel data lake FAQ
On September 30, 2025, Microsoft announced the general availability of the Microsoft Sentinel data lake, designed to centralize and retain massive volumes of security data in open formats like delta parquet. By decoupling storage from compute, the data lake supports flexible querying, while offering unified data management and cost-effective retention. The Sentinel data lake is a game changer for security teams, serving as the foundational layer for agentic defense, deeper security insights and graph-based enrichment. In this blog we offer answers to many of the questions we’ve heard from our customers and partners. General questions 1. What is the Microsoft Sentinel data lake? Microsoft has expanded its industry-leading SIEM solution, Microsoft Sentinel, to include a unified, security data lake, designed to help optimize costs, simplify data management, and accelerate the adoption of AI in security operations. This modern data lake serves as the foundation for the Microsoft Sentinel platform. It has a cloud-native architecture and is purpose-built for security—bringing together all security data for greater visibility, deeper security analysis and contextual awareness. It provides affordable, long-term retention, allowing organizations to maintain robust security while effectively managing budgetary requirements. 2. What are the benefits of Sentinel data lake? Microsoft Sentinel data lake is designed for flexible analytics, cost management, and deeper security insights. It centralizes security data in an open format like delta parquet for easy access. This unified view enhances threat detection, investigation, and response across hybrid and multi-cloud environments. It introduces a disaggregated storage and compute pricing model, allowing customers to store massive volumes of security data at a fraction of the cost compared to traditional SIEM solutions. It allows multiple analytics engines like Kusto, Spark, and ML to run on a single data copy, simplifying management, reducing costs, and supporting deeper security analysis. It integrates with GitHub Copilot and VS Code empowering SOC teams to automate enrichment, anomaly detection, and forensic analysis. It supports AI agents via the MCP server, allowing tools like GitHub Copilot to query and automate security tasks. The MCP Server layer brings intelligence to the data, offering Semantic Search, Query Tools, and Custom Analysis capabilities that make it easier to extract insights and automate workflows. Customers also benefit from streamlined onboarding, intuitive table management, and scalable multi-tenant support, making it ideal for MSSPs and large enterprises. The Sentinel data lake is purpose built for security workloads, ensuring that processes from ingestion to analytics meet cybersecurity requirements. 3. Is the Sentinel data lake generally available? Yes. The Sentinel data lake is generally available (GA) starting September 30, 2025. To learn more, see GA announcement blog. 4. What happens to Microsoft Sentinel SIEM? Microsoft is expanding Sentinel into an AI powered end-to-end security platform that includes SIEM and new platform capabilities - Security data lake, graph-powered analytics and MCP Server. SIEM remains a core component and will be actively developed and supported. Getting started 1. What are the prerequisites for Sentinel data lake? To get started: Connect your Sentinel workspace to Microsoft Defender prior to onboarding to Sentinel data lake. Once in the Defender experience see data lake onboarding documentation for next steps. Note: Sentinel is moving to the Microsoft Defender portal and the Sentinel Azure portal will be retired by July 2026. 2. I am a Sentinel-only customer, and not a Defender customer, can I use the Sentinel data lake? Yes. You must connect Sentinel to the Defender experience before onboarding to the Sentinel data lake. Microsoft Sentinel is generally available in the Microsoft Defender portal, with or without Microsoft Defender XDR or an E5 license. If you have created a log analytics workspace, enabled it for Sentinel and have the right Microsoft Entra roles (e.g. Global Administrator + Subscription Owner, Security Administrator + Sentinel Contributor), you can enable Sentinel in the Defender portal. For more details on how to connect Sentinel to Defender review these sources: Microsoft Sentinel in the Microsoft Defender portal 3. In what regions is Sentinel data lake available? For supported regions see: Geographical availability and data residency in Microsoft Sentinel | Azure Docs. 4. Is there an expected release date for Microsoft Sentinel data lake in Government clouds? While the exact date is not yet finalized, we anticipate support for these clouds soon. 5. How will URBAC and Entra RBAC work together to manage the data lake given there is no centralized model? Entra RBAC will provide broad access to the data lake (URBAC maps the right permissions to specific Entra role holders: GA/SA/SO/GR/SR). URBAC will become a centralized pane for configuring non-global delegated access to the data lake. For today, you will use this for the “default data lake” workspace. In the future, this will be enabled for non-default Sentinel workspaces as well – meaning all workspaces in the data lake can be managed here for data lake RBAC requirements. Azure RBAC on the Log Analytics (LA) workspace in the data lake is respected through URBAC as well today. If you already hold a built-in role like log analytics reader, you will be able to run interactive queries over the tables in that workspace. Or, if you hold log analytics contributor, you can read and manage table data. For more details see: Roles and permissions in the Microsoft Sentinel platform | Microsoft Learn Data ingestion and storage 1. How do I ingest data into the Sentinel data lake? To ingest data into the Sentinel data lake, you can use existing Sentinel data connectors or custom connectors to bring data from Microsoft and third-party sources. Data can be ingested into the analytic tier and/or data lake tier. Data ingested into the analytics tier is automatically mirrored to the lake, while lake-only ingestion is available for select tables. Data retention is configured in table management. Note: Certain tables do not support data lake-only ingestion via either API or data connector UI. See here for more information: Custom log tables. 2. What is Microsoft’s guidance on when to use analytics tier vs. the data lake tier? Sentinel data lake offers flexible, built-in data tiering (analytics and data lake tiers) to effectively meet diverse business use cases and achieve cost optimization goals. Analytics tier: Is ideal for high-performance, real-time, end-to-end detections, enrichments, investigation and interactive dashboards. Typically, high-fidelity data from EDRs, email gateways, identity, SaaS and cloud logs, threat intelligence (TI) should be ingested into the analytics tier. Data in the analytics tier is best monitored proactively with scheduled alerts and scheduled analytics to enable security detections Data in this tier is retained at no cost for up to 90 days by default, extendable to 2 years. A copy of the data in this tier is automatically available in the data lake tier at no extra cost, ensuring a unified copy of security data for both tiers. Data lake tier: Is designed for cost-effective, long-term storage. High-volume logs like NetFlow logs, TLS/SSL certificate logs, firewall logs and proxy logs are best suited for data lake tier. Customers can use these logs for historical analysis, compliance and auditing, incident response (IR), forensics over historical data, build tenant baselines, TI matching and then promote resulting insights into the analytics tier. Customers can run full Kusto queries, Spark Notebooks and scheduled jobs over a single copy of their data in the data lake. Customers can also search, enrich and restore data from the data lake tier to the analytics tier for full analytics. For more details see documentation. 3. What does it mean that a copy of all new analytics tier data will be available in the data lake? When Sentinel data lake is enabled, a copy of all new data ingested into the analytics tier is automatically duplicated into the data lake tier. This means customers don’t need to manually configure or manage this process—every new log or telemetry added to the analytics tier becomes instantly available in the data lake. This allows security teams to run advanced analytics, historical investigations, and machine learning models on a single, unified copy of data in the lake, while still using the analytics tier for real-time SOC workflows. It’s a seamless way to support both operational and long-term use cases—without duplicating effort or cost. 4. Is there any cost for retention in the analytics tier? You will get 90 days of analytics retention free. Simply set analytics retention to 90 days or less. Total retention setting – only the mirrored portion that overlaps with the free analytics retention is free in the data lake. Retaining data in the lake beyond the analytics retention period incurs additional storage costs. See documentation for more details: Manage data tiers and retention in Microsoft Sentinel | Microsoft Learn 5. What is the guidance for Microsoft Sentinel Basic and Auxiliary Logs customers? If you previously enabled Basic or Auxiliary Logs plan in Sentinel: You can view Basic Logs in the Defender portal but manage it from the Log Analytics workspace. To manage it in the Defender portal, you must change the plan from Basic to Analytics. Existing Auxiliary Log tables will be available in the data lake tier for use once the Sentinel data lake is enabled. Prior to the availability of Sentinel data lake, Auxiliary Logs provided a long-term retention solution for Sentinel SIEM. Now once the data lake is enabled, Auxiliary Log tables will be available in the Sentinel data lake for use with the data lake experiences. Billing for Auxiliary Logs will switch to Sentinel data lake meters. Microsoft Sentinel customers are recommended to start planning their data management strategy with the data lake. While Basic and auxiliary Logs are still available, they are not being enhanced further. Please plan on onboarding your security data to the Sentinel data lake. Azure Monitor customers can continue to use Basic and Auxiliary Logs for observability scenarios. 6. What happens to customers that already have Archive logs enabled? If a customer has already configured tables for Archive retention, those settings will be inherited by the Sentinel data lake and will not change. Data in the Archive logs will continue to be accessible through Sentinel search and restore experiences. Mirrored data (in the data lake) will be accessible via lake explorer and notebook jobs. Example: If a customer has 12 months of total retention enabled on a table, 2 months after enabling ingestion into the Sentinel data lake, the customer will still have access to 12 months of archived data (through Sentinel search and restore experiences), but access to only 2 months of data in the data lake (since the data lake was enabled). Key considerations for customers that currently have Archive logs enabled: The existing archive will remain, with new data ingested into the data lake going forward; previously stored archive data will not be backfilled into the lake. Archive logs will continue to be accessible via the Search and Restore tab under Sentinel. If analytics and data lake mode are enabled on table, which is the default setting for analytics tables when Sentinel data lake is enabled, data will continue to be ingested into the Sentinel data lake and archive going forward. There will only be one retention billing meter going forward. Archive will continue to be accessible via Search and Restore. If Sentinel data lake-only mode is enabled on table, new data will be ingested only into the data lake; any data that’s not already in the Sentinel data lake won’t be migrated/backfilled. Data that was previously ingested under the archive plan will be accessible via Search and Restore. 7. What is the guidance for customers using Azure Data Explorer (ADX) alongside Microsoft Sentinel? Some customers might have set up ADX cluster to augment their Sentinel deployment. Customers can choose to continue using that setup and gradually migrate to Sentinel data lake for new data to receive the benefits of a fully managed data lake. For all new implementations it is recommended to use the Sentinel data lake. 8. What happens to the Defender XDR data after enabling Sentinel data lake? By default, Defender XDR retains threat hunting data in the XDR default tier, which includes 30 days of analytics retention, which is included in the XDR license. You can extend the table retention period for supported Defender XDR tables beyond 30 days. For more information see Manage XDR data in Microsoft Sentinel. Note: Today you can't ingest XDR tables directly to the data lake tier without ingesting into the analytics tier first. 9. Are there any special considerations for XDR tables? Yes, XDR tables are unique in that they are available for querying in advanced hunting by default for 30 days. To retain data beyond this period, an explicit change to the retention setting is required, either by extending the analytics tier retention or the total retention period. A list of XDR advanced hunting tables supported by Sentinel are documented here: Connect Microsoft Defender XDR data to Microsoft Sentinel | Microsoft Learn. KQL queries and jobs 1. Is KQL and Notebook supported over the Sentinel data lake? Yes, via the data lake KQL query experience along with a fully managed Notebook experience which enables spark-based big data analytics over a single copy of all your security data. Customers can run queries across any time range of data in their Sentinel data lake. In the future, this will be extended to enable SQL query over lake as well. 2. Why are there two different places to run KQL queries in Sentinel experience? Consolidating advanced hunting and KQL Explorer user interfaces is on the roadmap. Security analysts will benefit from unified query experience across both analytics and data lake tiers. 3. Where is the output from KQL jobs stored? KQL jobs are written into existing or new analytics tier table. 4. Is it possible to run KQL queries on multiple data lake tables? Yes, you can run KQL interactive queries and jobs using operators like join or union. 5. Can KQL queries (either interactive or via KQL jobs) join data across multiple workspaces? Yes, security teams can run multi-workspace KQL queries for broader threat correlation. Pricing and billing 1. How does a customer pay for Sentinel data lake? Sentinel data lake is a consumption-based service with disaggregated storage and compute business model. Customers continue to pay for ingestion. Customers set up billing as a part of their onboarding for storage and analytics over data in the data lake (e.g. Queries, KQL or Notebook Jobs). See Sentinel pricing page for more details. 2. What are the pricing components for Sentinel data lake? Sentinel data lake offers a flexible pricing model designed to optimize security coverage and costs. For specific meter definitions, see documentation. 3. What are the billing updates at GA? We are enabling data compression billed with a simple and uniform data compression rate of 6:1 across all data sources, applicable only to data lake storage. Starting October 1, 2025, the data storage billing begins on the first day data is stored. To support ingestion and standardization of diverse data sources, we are introducing a new Data Processing feature that applies a $0.10 per GB charge for all uncompressed data ingested into the data lake for tables configured for data lake only retention. (does not apply to tables configured for both analytic and data lake tier retention). 4. How is retention billed for tables that use data lake-only ingestion & retention? During the public preview, data lake-only tables included the first 30 days of retention at no cost. At GA, storage costs will be billed. In addition, when retention billing switches to using compressed data size (instead of ingested size), this will change, and charges will apply for the entire retention period. Because billing will be based on compressed data size, customers can expect significant savings on storage costs. 5. Does “Data processing” meter apply to analytics tier data duplicated in the data lake? No. 6. What happens to billing for customers that activate Sentinel data lake on a table with archive logs enabled? Customers will automatically be billed using the data lake storage meter. Note: This means that customers will be charged using the 6X compression rate for data lake retention. 7. How do I control my Sentinel data lake costs? Sentinel is billed based on consumption and prices vary based on usage. An important tool in managing the majority of the cost is usage of analytics “Commitment Tiers”. The data lake complements this strategy for higher-volume data like network and firewall data to reduce analytics tier costs. Use the Azure pricing calculator and the Sentinel pricing page to estimate costs and understand pricing. 8. How do I manage Sentinel data lake costs? We are introducing a new cost management experience (public preview) to help customers with cost predictability, billing transparency, and operational efficiency. These in-product reports provide customers with insights into usage trends over time, enabling them to identify cost drivers and optimize data retention and processing strategies. Customers will also be able to set usage-based alerts on specific meters to monitor and control costs. For example, you can receive alerts when query or notebook usage passes set limits, helping avoid unexpected expenses and manage budgets. See documentation to learn more. 9. If I’m an Auxiliary Logs customer, how will onboarding to the Sentinel data lake affect my billing? Once a workspace is onboarded to Sentinel data lake, all Auxiliary Logs meters will be replaced by new data lake meters. Thank you Thank you to our customers and partners for your continued trust and collaboration. Your feedback drives our innovation, and we’re excited to keep evolving Microsoft Sentinel to meet your security needs. If you have any questions, please don’t hesitate to reach out—we’re here to support you every step of the way.393Views1like3CommentsMonthly news - October 2025
Microsoft Defender Monthly news - October 2025 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 September 2025. Defender for Cloud has it's own Monthly News post, have a look at their blog space. ⏰ Microsoft Ignite 2025 November 18-20, register now! 🚀 New Virtual Ninja Show episodes: Defender for Endpoint: Customize settings for optimum performance The new Defender for Identity sensor explained Expanding Microsoft Sentinel UEBA Transitioning the Sentinel SIEM experience from Azure to the Defender portal Microsoft Defender Move your Microsoft Sentinel experience into Microsoft Defender to streamline security operations into a single, AI-powered interface. This move enhances analyst efficiency, integrates threat insights, and improves response times through automation and advanced posture management. Customers are encouraged to begin planning their migration now to ensure a smooth transition and maximize the benefits of the new experience. Learn more about panning your move to the Defender portal here. Microsoft Defender delivered 242% return on investment over three years. The latest 2025 commissioned Forrester Consulting Total Economic Impact™ (TEI) study reveals a 242% ROI over three years for organizations that chose Microsoft Defender. Read more in our blog. Custom detection rules get a boost. If you are a Microsoft Sentinel user and have connected your Sentinel workspace to Microsoft Defender, you are probably more familiar with analytics rules in Microsoft Sentinel and are looking to explore the capabilities and benefits of custom detections. Understanding and leveraging custom detection rules can significantly enhance your organization's security posture. This blog will delve into the benefits of custom detections and showcase scenarios that highlight their capabilities, helping you make the most of this robust feature. (Public Preview) In advanced hunting, you can now hunt using the hunting graph, which renders rendering predefined threat scenarios as interactive graphs. (Public Preview) You can investigate incidents using Blast radius analysis, which is an advanced graph visualization built on the Microsoft Sentinel data lake and graph infrastructure. This feature generates an interactive graph showing possible propagation paths from the selected node to predefined critical targets scoped to the user’s permissions. Microsoft Defender for Cloud Apps (Public Preview) Protect Copilot Studio AI Agents in Real Time with Microsoft Defender. Microsoft Defender offers real-time protection during runtime for AI agents built with Microsoft Copilot Studio. This capability automatically blocks the agent’s response during runtime if a suspicious behavior like a prompt injection attack is detected, and notifies security teams with a detailed alert in the Microsoft Defender portal. Learn more about it in this blog. Protect against OAuth Attacks in Salesforce with Microsoft Defender. In this blog, we will delve only into one of the Salesforce OAuth attack campaign and provide guidance on how organizations can use Microsoft Defender to protect against this and similar SaaS attack campaigns. Microsoft Defender for Identity Defender for Identity data centers are now also deployed in the United Arab Emirates, North and Central regions. For the most current list of regional deployments, see Defender for Identity data locations. (Public Preview) We are excited to announce the availability of a new Graph-based API for managing unified agent server actions in Defender for Identity. This capability is currently in preview and available in API Beta version. This API allows customers to: Monitor the status of unified agent servers Enable or disable the automatic activation of eligible servers Activate or deactivate the agent on eligible servers For more information, see Managing unified agent actions through Graph API. Several Defender for Identity detections are being updated to reduce noise and improve accuracy, making alerts more reliable and actionable. As the rollout continues, you might see a decrease in the number of alerts raised. Learn more on our docs page. We've added a new tab on the Identity profile page that contains all active identity-related identity security posture assessments (ISPMs). This feature consolidates all identity-specific security posture assessments into a single contextual view, helping security teams quickly spot weaknesses and take targeted actions. Learn more on our docs page. (Public Preview) Defender for Identity supports the Unified connectors experience, starting with the Okta Single Sign-On connector. This enables Defender for Identity to collect Okta system logs once and share them across supported Microsoft security products, reducing API usage and improving connector efficiency. For more information, see: Connect Okta to Microsoft Defender for Identity Microsoft Defender for Office 365 Near real-time URL protection in Teams messages: - Known, malicious URLs in Teams messages are delivered with a warning. Messages found to contain malicious URLs up to 48 hours after delivery also receive a warning. The warning is added to messages in internal and external chats and channels for all URL verdicts (not just malware or high confidence phishing). Users can report external and intra-org Microsoft Teams messages as non-malicious (not a security risk) from the following locations: Chats Standard, shared, and private channels Meeting conversations User reported settings determine whether reported messages are sent to the specified reporting mailbox, to Microsoft, or both. Also added support for Teams message reporting on Teams mobile client. Microsoft Security Exposure Management Cloud Attack Paths now reflect real, externally driven and exploitable risks that adversaries could use to compromise your organization, helping you cut through the noise and act faster. The paths now focus on external entry points and how attackers could progress through your environment reaching business-critical targets. Read more about it in this blog: Refining Attack Paths: Prioritizing Real-World, Exploitable Threats The legacy Azure AD Connect asset rule has been removed from Critical Assets. Its associated device role, AzureADConnectServer, will be deprecated in December 2025. Ensure all relevant custom rules are transitioned to use the new device role, EntraConnectServer, to maintain compliance and visibility. For more information, see Predefined classification. New predefined classifications: predefined Device classification rules for SharePoint Server and Microsoft Entra ID Cloud Sync were added to the critical assets list. For more information, see Predefined classification. We have added new data connectors for Wiz and Palo Alto Prisma. These connectors enable seamless integration of vulnerability and asset data from leading cloud security platforms into Microsoft Security Exposure Management, providing enhanced visibility and context for your environments. For more information, see: Wiz data connector, Palo Alto Prisma data connector. Microsoft Security Blogs https://www.microsoft.com/en-us/security/blog/2025/09/24/ai-vs-ai-detecting-an-ai-obfuscated-phishing-campaign/ Microsoft Threat Intelligence recently detected and blocked a credential phishing campaign that likely used AI-generated code to obfuscate its payload and evade traditional defenses, demonstrating a broader trend of attackers leveraging AI to increase the effectiveness of their operations and underscoring the need for defenders to understand and anticipate AI-driven threats. XCSSET evolves again: Analyzing the latest updates to XCSSET’s inventory Microsoft Threat Intelligence has uncovered a new variant of the XCSSET malware, which is designed to infect Xcode projects, typically used by software developers building Apple or macOS-related applications.218Views0likes0CommentsEmpowering national SOCs with industry-leading, AI-powered cyber defense- Tech Community Live!
Cyberattacks on government entities can have significant impacts, potentially disrupting essential infrastructure, government functions, and economic stability. Join us to learn how Microsoft Sentinel's innovations and AI-powered insights can help safeguard national security. Ask your questions down below and the on-camera Subject Matter Experts will do their best to answer during the live hour after their presentation!3.2KViews12likes22CommentsMicrosoft Sentinel Data Tiering Best Practices - Tech Community Live!
Discover the power of the new Auxiliary logs tier (Public Preview) and learn how to use Summary rules (Public Preview) to summarize data from any log tier in Microsoft Sentinel and Log Analytics. We’ll explore the potential of these features and provide you with practical ideas and use cases to help you save on ingestion costs and extract more value from your verbose logs. Ask your questions down below and the on-camera Subject Matter Experts will do their best to answer during the live hour after their presentation!3.9KViews3likes23CommentsIntroducing Microsoft Security Store
Security is being reengineered for the AI era—moving beyond static, rulebound controls and after-the-fact response toward platform-led, machine-speed defense. We recognize that defending against modern threats requires the full strength of an ecosystem, combining our unique expertise and shared threat intelligence. But with so many options out there, it’s tough for security professionals to cut through the noise, and even tougher to navigate long procurement cycles and stitch together tools and data before seeing meaningful improvements. That’s why we built Microsoft Security Store - a storefront designed for security professionals to discover, buy, and deploy security SaaS solutions and AI agents from our ecosystem partners such as Darktrace, Illumio, and BlueVoyant. Security SaaS solutions and AI agents on Security Store integrate with Microsoft Security products, including Sentinel platform, to enhance end-to-end protection. These integrated solutions and agents collaborate intelligently, sharing insights and leveraging AI to enhance critical security tasks like triage, threat hunting, and access management. In Security Store, you can: Buy with confidence – Explore solutions and agents that are validated to integrate with Microsoft Security products, so you know they’ll work in your environment. Listings are organized to make it easy for security professionals to find what’s relevant to their needs. For example, you can filter solutions based on how they integrate with your existing Microsoft Security products. You can also browse listings based on their NIST Cybersecurity Framework functions, covering everything from network security to compliance automation — helping you quickly identify which solutions strengthen the areas that matter most to your security posture. Simplify purchasing – Buy solutions and agents with your existing Microsoft billing account without any additional payment setup. For Azure benefit-eligible offers, eligible purchases contribute to your cloud consumption commitments. You can also purchase negotiated deals through private offers. Accelerate time to value – Deploy agents and their dependencies in just a few steps and start getting value from AI in minutes. Partners offer ready-to-use AI agents that can triage alerts at scale, analyze and retrieve investigation insights in real time, and surface posture and detection gaps with actionable recommendations. A rich ecosystem of solutions and AI agents to elevate security posture In Security Store, you’ll find solutions covering every corner of cybersecurity—threat protection, data security and governance, identity and device management, and more. To give you a flavor of what is available, here are some of the exciting solutions on the store: Darktrace’s ActiveAI Security SaaS solution integrates with Microsoft Security to extend self-learning AI across a customer's entire digital estate, helping detect anomalies and stop novel attacks before they spread. The Darktrace Email Analysis Agent helps SOC teams triage and threat hunt suspicious emails by automating detection of risky attachments, links, and user behaviors using Darktrace Self-Learning AI, integrated with Microsoft Defender and Security Copilot. This unified approach highlights anomalous properties and indicators of compromise, enabling proactive threat hunting and faster, more accurate response. Illumio for Microsoft Sentinel combines Illumio Insights with Microsoft Sentinel data lake and Security Copilot to enhance detection and response to cyber threats. It fuses data from Illumio and all the other sources feeding into Sentinel to deliver a unified view of threats across millions of workloads. AI-driven breach containment from Illumio gives SOC analysts, incident responders, and threat hunters unified visibility into lateral traffic threats and attack paths across hybrid and multi-cloud environments, to reduce alert fatigue, prioritize threat investigation, and instantly isolate workloads. Netskope’s Security Service Edge (SSE) platform integrates with Microsoft M365, Defender, Sentinel, Entra and Purview for identity-driven, label-aware protection across cloud, web, and private apps. Netskope's inline controls (SWG, CASB, ZTNA) and advanced DLP, with Entra signals and Conditional Access, provide real-time, context-rich policies based on user, device, and risk. Telemetry and incidents flow into Defender and Sentinel for automated enrichment and response, ensuring unified visibility, faster investigations, and consistent Zero Trust protection for cloud, data, and AI everywhere. PERFORMANTA Email Analysis Agent automates deep investigations into email threats, analyzing metadata (headers, indicators, attachments) against threat intelligence to expose phishing attempts. Complementing this, the IAM Supervisor Agent triages identity risks by scrutinizing user activity for signs of credential theft, privilege misuse, or unusual behavior. These agents deliver unified, evidence-backed reports directly to you, providing instant clarity and slashing incident response time. Tanium Autonomous Endpoint Management (AEM) pairs realtime endpoint visibility with AI-driven automation to keep IT environments healthy and secure at scale. Tanium is integrated with the Microsoft Security suite—including Microsoft Sentinel, Defender for Endpoint, Entra ID, Intune, and Security Copilot. Tanium streams current state telemetry into Microsoft’s security and AI platforms and lets analysts pivot from investigation to remediation without tool switching. Tanium even executes remediation actions from the Sentinel console. The Tanium Security Triage Agent accelerates alert triage, enabling security teams to make swift, informed decisions using Tanium Threat Response alerts and real-time endpoint data. Walkthrough of Microsoft Security Store Now that you’ve seen the types of solutions available in Security Store, let’s walk through how to find the right one for your organization. You can get started by going to the Microsoft Security Store portal. From there, you can search and browse solutions that integrate with Microsoft Security products, including a dedicated section for AI agents—all in one place. If you are using Microsoft Security Copilot, you can also open the store from within Security Copilot to find AI agents - read more here. Solutions are grouped by how they align with industry frameworks like NIST CSF 2.0, making it easier to see which areas of security each one supports. You can also filter by integration type—e.g., Defender, Sentinel, Entra, or Purview—and by compliance certifications to narrow results to what fits your environment. To explore a solution, click into its detail page to view descriptions, screenshots, integration details, and pricing. For AI agents, you’ll also see the tasks they perform, the inputs they require, and the outputs they produce —so you know what to expect before you deploy. Every listing goes through a review process that includes partner verification, security scans on code packages stored in a secure registry to protect against malware, and validation that integrations with Microsoft Security products work as intended. Customers with the right permissions can purchase agents and SaaS solutions directly through Security Store. The process is simple: choose a partner solution or AI agent and complete the purchase in just a few clicks using your existing Microsoft billing account—no new payment setup required. Qualifying SaaS purchases also count toward your Microsoft Azure Consumption Commitment (MACC), helping accelerate budget approvals while adding the security capabilities your organization needs. Security and IT admins can deploy solutions directly from Security Store in just a few steps through a guided experience. The deployment process automatically provisions the resources each solution needs—such as Security Copilot agents and Microsoft Sentinel data lake notebook jobs—so you don’t have to do so manually. Agents are deployed into Security Copilot, which is built with security in mind, providing controls like granular agent permissions and audit trails, giving admins visibility and governance. Once deployment is complete, your agent is ready to configure and use so you can start applying AI to expand detection coverage, respond faster, and improve operational efficiency. Security and IT admins can view and manage all purchased solutions from the “My Solutions” page and easily navigate to Microsoft Cost Management tools to track spending and manage subscriptions. Partners: grow your business with Microsoft For security partners, Security Store opens a powerful new channel to reach customers, monetize differentiated solutions, and grow with Microsoft. We will showcase select solutions across relevant Microsoft Security experiences, starting with Security Copilot, so your offerings appear in the right context for the right audience. You can monetize both SaaS solutions and AI agents through built-in commerce capabilities, while tapping into Microsoft’s go-to-market incentives. For agent builders, it’s even simpler—we handle the entire commerce lifecycle, including billing and entitlement, so you don’t have to build any infrastructure. You focus on embedding your security expertise into the agent, and we take care of the rest to deliver a seamless purchase experience for customers. Security Store is built on top of Microsoft Marketplace, which means partners publish their solution or agent through the Microsoft Partner Center - the central hub for managing all marketplace offers. From there, create or update your offer with details about how your solution integrates with Microsoft Security so customers can easily discover it in Security Store. Next, upload your deployable package to the Security Store registry, which is encrypted for protection. Then define your license model, terms, and pricing so customers know exactly what to expect. Before your offer goes live, it goes through certification checks that include malware and virus scans, schema validation, and solution validation. These steps help give customers confidence that your solutions meet Microsoft’s integration standards. Get started today By creating a storefront optimized for security professionals, we are making it simple to find, buy, and deploy solutions and AI agents that work together. Microsoft Security Store helps you put the right AI‑powered tools in place so your team can focus on what matters most—defending against attackers with speed and confidence. Get started today by visiting Microsoft Security Store. If you’re a partner looking to grow your business with Microsoft, start by visiting Microsoft Security Store - Partner with Microsoft to become a partner. Partners can list their solution or agent if their solution has a qualifying integration with Microsoft Security products, such as a Sentinel connector or Security Copilot agent, or another qualifying MISA solution integration. You can learn more about qualifying integrations and the listing process in our documentation here.Microsoft Sentinel data lake is now generally available
Security is being reengineered for the AI era, shifting from static controls to fast, platform-driven defense. Traditional tools, scattered data, and outdated systems struggle against modern threats. An AI-ready, data-first foundation is needed to unify telemetry, standardize agent access, and enable autonomous responses while ensuring humans are in command of strategy and high-impact investigations. Security teams already anchor their operations around SIEMs for comprehensive visibility. We're building on that foundation by evolving Microsoft Sentinel into both the SIEM and the platform for agentic defense—connecting analytics and context across ecosystems. Today, we’re introducing new platform capabilities that build on Sentinel data lake: Sentinel graph for deeper insight and context; an MCP server and tools to make data agent ready; new developer capabilities; and a Security Store for effortless discovery and deployment—so protection accelerates to machine speed while analysts do their best work. We’ve reached a major milestone in our journey to modernize security operations — Microsoft Sentinel data lake is now generally available. This fully managed, cloud-native data lake is redefining how security teams manage, analyze, and act on their data cost-effectively. Since its introduction, organizations across sectors are embracing Sentinel data lake for its transformative impact on security operations. Customers consistently highlight its ability to unify security data from diverse sources, enabling enhanced threat detection and investigation. Many cite cost efficiency as a key benefit, with tiered storage and flexible retention, helping reduce costs. With petabytes of data already ingested, users are gaining real-time and historical insights at scale. "With Microsoft Sentinel data lake integration, we now have a scalable and cost-efficient solution for retaining Microsoft Sentinel data for long-term retention. This empowers our security and compliance teams with seamless access to historical telemetry data right within the data lake explorer and Jupyter notebooks - enabling advanced threat hunting, forensic analysis, and AI-powered insights at scale" Farhan Nadeem, Senior Security Engineer Government of Nunavut Industry partners also commend its role in modernizing SOC workflows and accelerating AI-driven analytics. “Microsoft Sentinel data lake amplifies BlueVoyant’s ability to transform security operations into a mature, intelligence-driven discipline. It preserves institutional memory across years of telemetry, which empowers advanced threat hunting strategies that evolve with time. Security teams can validate which data sources yield actionable insights, uncover persistent attack patterns, and retain high-value indicators that support long-term strategic advantage.” Milan Patel, CRO BlueVoyant Microsoft Sentinel data lake use-cases There are many powerful ways customers are unlocking value with Sentinel data lake—here are just a few impactful examples.: Threat investigations over extended timelines: Security analysts query data older than 90 days to uncover slow-moving attacks—like brute-force and password spray campaigns—that span accounts and geographies. Behavioral baselining for deeper insights: SOC engineers build time-series models using months of sign-in logs to establish a standard of normal behavior and identify unusual patterns, such as credential abuse or lateral movement. Alert enrichment: SOC teams correlate alerts with Firewall and Netflow data, often stored only in the data lake, reducing false positives and increasing alert accuracy. Retrospective threat hunting with new indicators of compromise (IOCs): Threat intelligence teams react to emerging IOCs by running historical queries across the data lake, enabling rapid and informed response. ML-Powered insights: SOC engineers use Spark Notebooks to build and operationalize custom machine learning models for anomaly detection, alert enrichment, and predictive analytics. The Sentinel data lake is more than a storage solution—it’s the foundation for modern, AI-powered security operations. Whether you're scaling your SOC, building deeper analytics, or preparing for future threats, the Sentinel data lake is ready to support your journey. What’s new Regional expansion In light of strong customer demand in public preview, at GA we are expanding Sentinel data lake availability to additional regions. These new regions will roll out progressively over the coming weeks. For more information, see documentation. Flexible data ingestion and management With over 350 native connectors, SOC teams can seamlessly ingest both structured and semi-structured data at scale. Data is automatically mirrored from the analytics tier to the data lake tier, at no additional cost, ensuring a single, unified copy is available for diverse use cases across security operations. Since the public preview of Microsoft Sentinel data lake, we've launched 45 new connectors built on the scalable and performant Codeless Connector Framework (CCF), including connectors for: GCP: SQL, DNS, VPC Flow, Resource Manager, IAM, Apigee AWS: Security Hub findings, Route53 DNS Others: Alibaba Cloud, Oracle, Salesforce, Snowflake, Cisco Sentinel’s connector ecosystem is designed to help security teams seamlessly unify signals across hybrid environments, without the need for heavy engineering effort. Explore the full list of connectors in our documentation here. App Assure Microsoft Sentinel data lake promise As part of our commitment to customer success, we are expanding the App Assure Microsoft Sentinel promise to Sentinel data lake. This means customers can confidently onboard their data, knowing that App Assure stands ready to help resolve connector issues such as replacing deprecated APIs with updated ones, and accelerating new integrations. Whether you're working with existing Independent Software Vendor (ISV) solutions or building new ones, App Assure will collaborate directly with ISVs to ensure seamless data ingestion into the lake. This promise reinforces our dedication to delivering reliable, scalable, and secure security operations, backed by engineering support and a thriving partner ecosystem. Cost management and billing We are introducing new cost management features in public preview to help customers with cost predictability, billing transparency, and operational efficiency. Customers can set usage-based alerts on specific meters to monitor and control costs. For example, you can receive alerts when query or notebook usage passes set limits, helping avoid unexpected expenses and manage budgets. In-product reports provide customers with insights into usage trends over time, enabling them to identify cost drivers and optimize data retention and processing strategies. To support the ingestion and standardization of diverse data sources, we are introducing a new Data Processing feature that applies a $0.10 per GB charge for all data as it is ingested into the data lake. This feature enables a broad array of transformations like redaction, splitting, filtering and normalizing data. This feature was not billed during public preview but will be chargeable at GA starting October 1,2025. Data lake ingestion charges of $0.05 per GB will apply to Entra asset data; starting October 1, 2025. This was previously not billed during public preview. Retaining security data to perform deep analytics and investigations is crucial for defending against threats. To help enable customers to retain all their security data for extended periods cost effectively, data lake storage, including asset data storage, is now billed with a simple and uniform data compression rate of 6:1 across all data sources. Please refer to Plan costs and understand Microsoft Sentinel pricing and billing article for more information. For detailed prerequisites and instructions on configuring and managing asset connectors, refer to the official documentation: Asset data in Microsoft Sentinel data lake. KQL and Notebook enhancements We are introducing several enhancements to our data lake analytics capabilities with an upgraded KQL and notebook experience. Security teams can now run multi-workspace KQL queries for broader threat correlation and schedule KQL jobs more frequently. Frequent KQL jobs enable SOC teams to automate historical threat intelligence matching, summarize alert trends, and aggregate signals across workspaces. For example, schedule recurring jobs to scan for matches against newly ingested IOCs, helping uncover threats that were previously undetected and strengthening threat hunting and investigation workflows. The enhanced Jobs page offers operational clarity for SOC teams with a comprehensive view into job health and activity. At the top, a summary dashboard provides instant visibility into key metrics, total jobs, completions, and failures, helping teams quickly assess job health. A filterable list view displays essential details such as job names, status, frequency, and last run information, enabling quick prioritization and triage. For more detailed diagnostics, users can view individual jobs to access job runs telemetry such as job run duration, row count, and additional historical execution trends, providing additional visibility. Notebooks are receiving a significant upgrade, offering streamlined user experience for querying the data lake. Users now benefit from IntelliSense support for syntax and table names, making query authoring faster and more intuitive. They can also configure custom compute session timeouts and warning windows to better manage resources. Scheduling notebooks as jobs is now simpler, and users can leverage GitHub Copilot for intelligent assistance throughout the process. Together, these KQL and notebook improvements deliver deeper, more customizable analytics, helping customers unlock richer insights, accelerate threat response, and scale securely across diverse environments. Powering agentic defense Data centralization powers AI agents and automation to access comprehensive, historical, and real-time data for advanced analytics, anomaly detection, and autonomous threat response. Support for tools like KQL queries, Spark notebooks, and machine learning models in the data lake, allows agentic systems to continuously learn, adapt, and act on emerging threats. Integration with Security Copilot and MCP Server further enhances agentic defense, enabling smarter, faster, and context-rich security operations—all built on the foundation of Sentinel’s unified data lake. Microsoft Sentinel 50 GB commitment tier promotional pricing To make Microsoft Sentinel more accessible to small and mid-sized customers, we are introducing a new 50 GB commitment tier in public preview, with promotional pricing offered from October 1, 2025, to March 31, 2026. Customers who choose the 50 GB commitment tier during this period will maintain their promotional rate until March 31, 2027. This offer is available in all regions where Microsoft Sentinel is sold, with regional variations in promotional pricing. It is accessible through EA, CSP, and Direct channels. The new 50 GB commitment tier details will be available starting October 1, 2025, on the Microsoft Sentinel pricing page. Thank you to our customers and partners We’re incredibly grateful for the continued partnership and collaboration from our customers and partners throughout this journey. Your feedback and trust have been instrumental in shaping Microsoft Sentinel data lake into what it is today. Thank you for being a part of this critical milestone—we’re excited to keep building together. Get started today By centralizing data, optimizing costs, expanding coverage, and enabling deep analytics, Microsoft Sentinel empowers security teams to operate smarter, faster, and more effectively. Get started with Microsoft Sentinel data lake today in the Microsoft Defender experience. To learn more, see: Microsoft Sentinel—AI-Powered Cloud SIEM & Platform Pricing: Pricing page, Plan costs and understand Microsoft Sentinel pricing and billing Documentation: Connect Sentinel to Defender, Jupyter notebooks in Microsoft Sentinel data lake, KQL and the Microsoft Sentinel data lake, Permissions for Microsoft Sentinel data lake, Manage data tiers and retention in Microsoft Defender experience Blogs: Sentinel data lake FAQ blog, Empowering defenders in the era of AI, Microsoft Sentinel graph announcement, App Assure Microsoft Sentinel data lake promiseIntroducing developer solutions for Microsoft Sentinel platform
Security is being reengineered for the AI era, moving beyond static, rule-bound controls and toward after-the-fact response toward platform-led, machine-speed defense. The challenge is clear: fragmented tools, sprawling signals, and legacy architectures that can’t match the velocity and scale of modern attacks. What’s needed is an AI-ready, data-first foundation - one that turns telemetry into a security graph, standardizes access for agents, and coordinates autonomous actions while keeping humans in command of strategy and high-impact investigations. Security teams already center operations on their SIEM for end-to-end visibility, and we’re advancing that foundation by evolving Microsoft Sentinel into both the SIEM and the platform for agentic defense—connecting analytics and context across ecosystems. And today, we’re introducing new platform capabilities that build on Sentinel data lake: Sentinel graph for deeper insight and context; Sentinel MCP server and tools to make data agent ready; new developer capabilities; and Security Store for effortless discovery and deployment—so protection accelerates to machine speed while analysts do their best work. Today, customers use a breadth of solutions to keep themselves secure. Each solution typically ingests, processes, and stores the security data it needs which means applications maintain identical copies of the same underlying data. This is painful for both customers and partners, who don’t want to build and maintain duplicate infrastructure and create data silos that make it difficult to counter sophisticated attacks. With today’s announcement, we’re directly addressing those challenges by giving partners the ability to create solutions that can reason over the single copy of the security data that each customer has in their Sentinel data lake instance. Partners can create AI solutions that use Sentinel and Security Copilot and distribute them in Microsoft Security Store to reach audiences, grow their revenue, and keep their customers safe. Sentinel already has a rich partner ecosystem with hundreds of SIEM solutions that include connectors, playbooks, and other content types. These new platform capabilities extend those solutions, creating opportunities for partners to address new scenarios and bring those solutions to market quickly since they don’t need to build complex data pipelines or store and process new data sets in their own infrastructure. For example, partners can use Sentinel connectors to bring their own data into the Sentinel data lake. They can create Jupyter notebook jobs in the updated Sentinel Visual Studio Code extension to analyze that data or take advantage of the new Model Context Protocol (MCP) server which makes the data understandable and accessible to AI agents in Security Copilot. With Security Copilot’s new vibe-coding capabilities, partners can create their agent in the same Sentinel Visual Studio Code extension or the environment of their choice. The solution can then be packaged and published to the new Microsoft Security Store, which gives partners an opportunity to expand their audience and grow their revenue while protecting more customers across the ecosystem. These capabilities are being embraced across our ecosystem by mature and emerging partners alike. Services partners such as Accenture and ISVs such as Zscaler and ServiceNow are already creating solutions that leverage the capabilities of the Sentinel platform. Partners have already brought several solutions to market using the integrated capabilities of the Sentinel platform: Illumio. Illumio for Microsoft Sentinel combines Illumio Insights with Microsoft Sentinel data lake and Security Copilot to revolutionize detection and response to cyber threats. It fuses data from Illumio and all the other sources feeding into Sentinel to deliver a unified view of threats, giving SOC analysts, incident responders, and threat hunters visibility and AI-driven breach containment capabilities for lateral traffic threats and attack paths across hybrid and multi-cloud environments. To learn more, visit Illumio for Microsoft Sentinel. OneTrust. OneTrust’s AI-ready governance platform enables 14,000 customers globally – including over half of the Fortune 500 – to accelerate innovation while ensuring responsible data use. Privacy and risk teams know that undiscovered personal data in their digital estate puts their business and customers at risk. OneTrust’s Privacy Risk Agent uses Security Copilot, Purview scan logs, Entra ID data, and Jupyter notebook jobs in the Sentinel data lake to automatically discover personal data, assess risk, and take mitigating actions. To learn more, visit here. Tanium. The Tanium Security Triage Agent accelerates alert triage using real-time endpoint intelligence from Tanium. Tanium intends to expand its agent to ingest contextual identity data from Microsoft Entra using Sentinel data lake. Discover how Tanium’s integrations empower IT and security teams to make faster, more informed decisions. Simbian. Simbian’s Threat Hunt Agent makes hunters more effective by automating the process of validating threat hunt hypotheses with AI. Threat hunters provide a hypothesis in natural language, and the Agent queries and analyzes the full breadth of data available in Sentinel data lake to validate the hypothesis and do deep investigation. Simbian's AI SOC Agent investigates and responds to security alerts from Sentinel, Defender, and other alert sources and also uses Sentinel data lake to enhance the depth of investigations. Learn more here. Lumen. Lumen’s Defender℠ Threat Feed for Microsoft Sentinel helps customers correlate known-bad artifacts with activity in their environment. Lumen’s Black Lotus Labs® harnesses unmatched network visibility and machine intelligence to produce high-confidence indicators that can be operationalized at scale for detection and investigation. Currently Lumen’s Defender℠ Threat Feed for Microsoft Sentinel is available as an invite only preview. To request an invite, reach out to the Lumen Defender Threat Feed Sales team. The updated Sentinel Visual Studio Code extension for Microsoft Sentinel The Sentinel Extension for Visual Studio code brings new AI and packaging capabilities on top of existing Jupyter notebook jobs to help developers efficiently create new solutions. Building with AI Impactful AI security solutions need access and understanding of relevant security data to address a scenario. The new Microsoft Sentinel Model Context Protocol (MCP) server makes data in Sentinel data lake AI-discoverable and understandable to agents so they can reason over it to generate powerful new insights. It integrates with the Sentinel VS Code extension so developers can use those tools to explore the data in the lake and have agents use those tools as they do their work. To learn more, read the Microsoft Sentinel MCP server announcement. Microsoft is also releasing MCP tools to make creating AI agents more straightforward. Developers can use Security Copilot’s MCP tools to create agents within either the Sentinel VS Code extension or the environment of their choice. They can also take advantage of the low code agent authoring experience right in the Security Copilot portal. To learn more about the Security Copilot pro code and low code agent authoring experiences visit the Security Copilot blog post on Building your own Security Copilot agents. Jupyter Notebook Jobs Jupyter notebooks jobs are an important part of the Sentinel data lake and were launched at our public preview a couple of months ago. See the documentation here for more details on Jupyter notebooks jobs and how they can be used in a solution. Note that when jobs write to the data lake, agents can use the Sentinel MCP tools to read and act on those results in the same way they’re able to read any data in the data lake. Packaging and Publishing Developers can now package solutions containing notebook jobs and Copilot agents so they can be distributed through the new Microsoft Security Store. With just a few clicks in the Sentinel VS Code extension, a developer can create a package which they can then upload to Security Store. Distribution and revenue opportunities with Security Store Sentinel platform solutions can be packaged and offered through the new Microsoft Security Store, which gives partners new ways to grow revenue and reach customers. Learn more about the ways Microsoft Security Store can help developers reach customers and grow revenue by visiting securitystore.microsoft.com. Getting started Developers can get started building powerful applications that bring together Sentinel data, Jupyter notebook jobs, and Security Copilot today: Become a partner to publish solutions to Microsoft Security Store Onboarding to Sentinel data lake Downloading the Sentinel Visual Studio Code extension Learn about Security Copilot news Learn about Microsoft Security StoreAnnouncing Microsoft Sentinel Model Context Protocol (MCP) server – Public Preview
Security is being reengineered for the AI era—moving beyond static, rulebound controls and after-the-fact response toward platform-led, machine-speed defense. The challenge is clear: fragmented tools, sprawling signals, and legacy architectures that can’t match the velocity and scale of modern attacks. What’s needed is an AI-ready, data-first foundation—one that turns telemetry into a security graph, standardizes access for agents, and coordinates autonomous actions while keeping humans in command of strategy and high-impact investigations. Security teams already center operations on their SIEM for end-to-end visibility, and we’re advancing that foundation by evolving Microsoft Sentinel into both the SIEM and the platform for agentic defense—connecting analytics and context across ecosystems. And now, we’re introducing new platform capabilities that build on Sentinel data lake: Sentinel graph for deeper insight and context; an MCP server and tools to make data agent ready; new developer capabilities; and Security Store for effortless discovery and deployment—so protection accelerates to machine speed while analysts do their best work. Introducing Sentinel MCP server We’re excited to announce the public preview of Microsoft Sentinel MCP (Model Context Protocol) server, a fully managed cloud service built on an open standard that lets AI agents seamlessly access the rich security context in your Sentinel data lake. Recent advances in large language models have enabled AI agents to perform reasoning—breaking down complex tasks, inferring patterns, and planning multistep actions, making them capable of autonomously performing business processes. To unlock this potential in cybersecurity, agents must operate with your organization’s real security context, not just public training data. Sentinel MCP server solves that by providing standardized, secure access to that context—across graph relationships, tabular telemetry, and vector embeddings—via reusable, natural language tools, enabling security teams to unlock the full potential of AI-driven automation and focus on what matters most. Why Model Context Protocol (MCP)? Model Context Protocol (MCP) is a rapidly growing open standard that allows AI models to securely communicate with external applications, services, and data sources through a well-structured interface. Think of MCP as a bridge that lets an AI agents understand and invoke an application’s capabilities. These capabilities are exposed as discrete “tools” with natural language inputs and outputs. The AI agent can autonomously choose the right tool (or combination of tools) for the task it needs to accomplish. In simpler terms, MCP standardizes how an AI talks to systems. Instead of developers writing custom connectors for each application, the MCP server presents a menu of available actions to the AI in a language it understands. This means an AI agent can discover what it can do (search data, run queries, trigger actions, etc.) and then execute those actions safely and intelligently. By adopting an open standard like MCP, Microsoft is ensuring that our AI integrations are interoperable and future-proof. Any AI application that speaks MCP can connect. Security Copilot offers built-in integration, while other MCP-compatible platforms can leverage your Sentinel data and services can quickly connect by simply adding a new MCP server and typing Sentinel’s MCP server URL. How to Get Started Sentinel MCP server is a fully managed service now available to all Sentinel data lake customers. If you are already onboarded to Sentinel data lake, you are ready to begin using MCP. Not using Sentinel data lake yet? Learn more here. Currently, you can connect to the Sentinel MCP server using Visual Studio Code (VS Code) with the GitHub Copilot add-on. Here’s a step-by-step guide: Open VS Code and authenticate with an account that has at least Security Reader role access (required to query the data lake via the Sentinel MCP server) Open the Command Palette in VS Code (Ctrl + Shift + P) Type or select “MCP: Add Server…” Choose “HTTP” (HTTP or Server-Sent Event) Enter the Sentinel MCP server URL: “https://sentinel.microsoft.com/mcp/data-exploration" When prompted, allow authentication with the Sentinel MCP server by clicking “Allow” Once connected, GitHub Copilot will be linked to Sentinel MCP server. Open the agent pane, set it to Agent mode (Ctrl + Shift + I), and you are ready to go. GitHub Copilot will autonomously identify and utilize Sentinel MCP tools as necessary. You can now experience how AI agents powered by the Sentinel MCP server access and utilize your security context using natural language, without knowing KQL, which tables to query and wrangle complex schemas. Try prompts like: “Find the top 3 users that are at risk and explain why they are at risk.” “Find sign-in failures in the last 24 hours and give me a brief summary of key findings.” “Identify devices that showed an outstanding amount of outgoing network connections.” To learn more about the existing capabilities of Sentinel MCP tools, refer to our documentation. Security Copilot will also feature native integration with Sentinel MCP server; this seamless connectivity will enhance autonomous security agents and the open prompting experience. Check out the Security Copilot blog for additional details. What’s coming next? The public preview of Sentinel MCP server marks the beginning of a new era in cybersecurity—one where AI agents operate with full context, precision, and autonomy. In the coming months, the MCP toolset will expand to support natural language access across tabular, graph, and embedding-based data, enabling agents to reason over both structured and unstructured signals. This evolution will dramatically boost agentic performance, allowing them to handle more complex tasks, surface deeper insights, and accelerate protection to machine speed. As we continue to build out this ecosystem, your feedback will be essential in shaping its future. Be sure to check out the Microsoft Secure for a deeper dive and live demo of Sentinel MCP server in action.1.9KViews2likes0Comments