Security Operations

47 Topics
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- Technical FAQ!","conversation":{"__ref":"Conversation:conversation:4189136"},"id":"message:4189136","revisionNum":9,"uid":4189136,"depth":0,"board":{"__ref":"Blog:board:MicrosoftSentinelBlog"},"author":{"__ref":"User:user:2553398"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" In this blog, we dive into some of the most common questions and share best practices to expedite resolution, bring more clarity, and save valuable troubleshooting time. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":23651},"postTime":"2024-07-11T09:03:28.757-07:00","lastPublishTime":"2024-10-21T09:27:02.501-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Introduction \n   \n If you are a security practitioner who uses Microsoft Sentinel in your daily workflows, and you have tried or are evaluating the unified security operations platform for your SOC – this blog is for you. With Microsoft Sentinel now Generally Available in the Microsoft Defender portal, as part of our unified security operations platform, it’s a great time to try and get started with a streamlined experience for the two products. \n   \n In this blog, we dive into some of the most common questions and share best practices to expedite resolution, bring more clarity, and save valuable troubleshooting time. \n   \n First, a brief overview if you are new to the unified security operations platform. Our vision of the platform is a solution that makes your job as a security practitioner easier, keeping you and your organizations safer. It is single pane of glass for all security operations – here you can seamlessly integrate SIEM, XDR, exposure management, and Copilot for Security. It’s your comprehensive hub for preventing, detecting, investigating, and responding to incidents across your digital estate—all from one centralized location. \n   \n Here are some of the most common questions and guidance when working with the unified platform. \n   \n Onboarding \n \n What role/permissions are required to connect a Microsoft Sentinel workspace to the unified platform? \n \n To connect or disconnect a Microsoft Sentinel workspace to the unified platform, you will need one of the following permissions and scopes: \n a. Owner rights for the Subscription AND Microsoft Sentinel Contributor rights for the Subscription or Resource Group or Log Analytics workspace. OR \n b. User Access Administrator for the Subscription AND Microsoft Sentinel Contributor for the Subscription or Resource Group or Log Analytics workspace. \n   \n 2. I see the following error message when trying to connect my Microsoft Sentinel workspace with the unified platform “couldn’t connect the workspace. Turn on the Defender XDR connector for incidents in Microsoft Sentinel first”. What to do? \n \n   \n   \n a. Microsoft Defender XDR (formerly named Microsoft 365 Defender) connector is one of the prerequisites for the onboarding, so if it hasn’t been configured, you will most likely see this message. The good thing is configuring the connector is a rather straightforward process. Follow these steps to configure the connector. \n   \n b. When configuring the connector, make sure to click on “Connect incidents & alerts” button. While Microsoft incident creation rules for the Microsoft Defender products will be turned off by default, if for some reason you don’t see them disabled, make sure to check this box “Turn off all Microsoft creation rules for these products. Recommended”. \n \n   \n \n What happens when I enable the Microsoft Defender XDR connector in Microsoft Sentinel? \n \n a. The Security incident creation rules are disabled by default. Incidents are created first in the unified portal, then synced back to Microsoft Sentinel. \n b. You may notice a delay of up to 5 minutes for incidents to show up in Microsoft Sentinel. We are working on reducing this latency. \n   \n 4. Why don’t I see all my Microsoft Sentinel workspaces in the unified portal? \n You can only see Microsoft Sentinel workspaces that you have permission to onboard. Refer to question 1 for the specific permissions. \n   \n Alerts, Incidents, and Correlation \n 1. I noticed Microsoft Defender XDR incidents are delayed in Microsoft Sentinel. What is the expected delay for incidents to show up in Microsoft Sentinel? \n It may take up to 5 minutes for Microsoft Defender incidents to show in Microsoft Sentinel. We are working on reducing this latency. Stay tuned through our customer connection program for the latest updates. \n   \n 2. Does that delay in incidents also delay Automatic Attack Disruption? \n No, it will not. The delay for incidents is from Microsoft Defender to Microsoft Sentinel. Attack Disruption occurs within the unified platform.   \n   \n 3. Could that be up to 5 minutes delayed in the Microsoft Sentinel to trigger playbooks too? \n Yes. Currently this delay affects both scenarios for playbooks - whether a playbook is automatically invoked from an automation rule or manually invoked. As mentioned, we are working on reducing the latency. \n   \n 4. I am seeing duplication of incidents and alerts in Microsoft Sentinel and Microsoft Defender XDR. How to avoid this? \n The duplication is likely due to the misconfiguration of the Microsoft Defender XDR connector. Please check the Microsoft Defender XDR connector configuration first to make sure the Microsoft incident creation rules are turned off for the Microsoft Defender products. \n   \n 5. What are synced bi-directional for incidents? \n Incident status, tags, resolution, closing reasons, closing comments are bi-directionally synced. \n   \n 6. Microsoft Defender has 14 Incident Classifications; Microsoft Sentinel has 5.  How are they mapped? \n We are working on aligning the classifications. Stay tuned through our customer connection program for the latest updates. \n   \n \n Why and when does the incident auto-merging happen? \n \n a. Microsoft Defender XDR’s correlation activities don’t stop when incidents are created. Microsoft Defender XDR continues to detect commonalities and relationships between incidents, and between alerts across incidents. When two or more incidents are determined to be sufficiently alike, Microsoft Defender XDR merges the incidents into a single incident. \n b. The correlation engine merges the incident when common elements are detected, like: \n - Entities – like users, devices, mailboxes, and others \n - Artifacts – like files, processes, email senders, and others \n - Time frames \n - Sequence of events: For example, a malicious email click event that follows closely on a phishing email detection \n c. Refer to the documentation for more details on incident merging and correlation. \n   \n \n How does incident and alert correlation work in the unified platform? \n \n a. When the alert is sufficiently unique across all alert sources within a particular time frame, Microsoft Defender XDR creates a new incident and adds the alert to it. \n b. When the alert is sufficiently related to other alerts from the same source or across sources within a particular time frame, Microsoft Defender XDR adds the alert to an existing incident. \n   \n 9. What happens when incidents are merged? \n - Alerts contained in the abandoned incident are moved to the consolidated incident \n - Entities (assets etc.) follow the alerts they’re linked to \n - Tags are aggregated into the consolidated incident \n - Analytics rules recorded as involved in the creation of the abandoned incident are added to the rules recorded in the consolidated incident \n - Currently, comments and activity log entries in the abandoned incident are not moved to the consolidated incident and remain in the abandoned incident. \n   \n 10. When is incident correlation not happening? \n - One of the incidents has the status of \"Closed\". Incidents that are resolved will not be reopened. \n - The two incidents eligible for merging are assigned to two different people. \n - Merging the two incidents would raise the number of entities in the merged incident above the maximum allowed. \n - The two incidents contain devices in different device groups as defined by the organization. \n (Note: this condition is not in effect by default; it must be enabled.) \n   \n \n When should I unlink an alert? \n \n When you decide that the alert does not belong to the correlated incident, link the alert to another incident or create a new one. This will also help improve the correlation engine (in case of unexpected correlations). \n \n   \n Analytics/Custom Detections \n \n Does custom detection support entity mappings like in Analytics rules in Microsoft Sentinel? \n \n Currently no, but we are adding the features of analytic rules from Microsoft Sentinel such as more flexible entity mappings. Stay tuned through our customer connection program for the latest updates. \n   \n \n Does the unified platform support Fusion rules? \n \n The Fusion analytics rule, which creates incidents based on alert correlations made by the Fusion correlation engine, is disabled when you onboard Microsoft Sentinel to the unified security operations platform. \n The unified security operations platform uses Microsoft Defender XDR's incident-creation and correlation functionalities to replace those of the Fusion engine. \n   \n \n How can I create detection rules across Microsoft Sentinel and Defender XDR data? \n \n a. You can now create Custom Detection rules across the two datasets without having to ingest Microsoft Defender data into Sentinel, unless you need longer data retention. Advanced hunting in Microsoft Defender - Microsoft Defender XDR | Microsoft Learn. \n b. If your Defender XDR data is ingested into Microsoft Sentinel, you have the option to choose between Create custom detection and Create analytics rule. \n   \n Automation and Playbooks \n \n Will Automation rules work as normal? \n \n Automation rules will continue to work in the unified experience. However, there are some differences in the way automation functions work in the new experience. Please refer to the documentation for more information on the differences and changes. \n   \n \n What are some best practices for using automation rules in the unified platform? \n \n a. Use the condition “Analytic rule name” instead of the incident title or use the condition on a Tag. \n \n   \n b. In both the Azure portal and the unified security operations platform, for automation rule condition, use Alert product names instead of Incident provider. The reason is that in Sentinel standalone experience, all incidents have Microsoft XDR as the incident provider (the value in the providerName field). \n   \n \n   \n \n Will we be able to run a playbook as part of the actions of a custom detection rule? \n \n Yes, incidents created by custom detection rules are part of the Microsoft Defender XDR incidents which is supported by the “When incident is created” trigger in Automation. Please take note of some of the best practices documented when configuring the trigger condition. \n   \n APIs \n \n Can I still use the Microsoft Sentinel REST APIs with the unified platform? \n \n You can use most of the existing Microsoft Sentinel REST APIs; however, you should use the Microsoft Graph REST API queries for alerts and incidents \n List alerts_v2 - Microsoft Graph v1.0 | Microsoft Learn \n List incidents - Microsoft Graph v1.0 | Microsoft Learn \n   \n   \n Advanced hunting \n \n How do I bookmark a query in Advanced Hunting? \n \n There will be a new capability which is similar to bookmarks coming soon in the unified experience. Stay tuned through our customer connection program for the latest updates. \n   \n \n Can we query ADX data (with KQL adx() function) in Advanced Hunting? \n \n You can run a query that correlates Microsoft Sentinel data with ADX data using adx() in Advanced Hunting. Please note that the query of adx() needs to be correlated with tables from Microsoft Sentinel. This is in parity with what customers could run in Microsoft Sentinel today. \n   \n Data Retention \n \n Do I need to do anything additional with Retention in either Microsoft Sentinel or Microsoft Defender? \n \n The existing Sentinel data retention configurations remain unchanged. \n   \n \n Do I still need to ingest my Microsoft Defender XDR tables into Microsoft Sentinel? \n \n With the unified experience, you can query and correlate your Defender XDR logs with third-party logs from Microsoft Sentinel without ingesting the Microsoft Defender XDR logs into Microsoft Sentinel. Additionally, the same query of Microsoft Defender XDR and Microsoft Sentinel tables can be used in Microsoft Defender’s custom detection. Therefore, the primary reason for ingesting Microsoft Defender XDR data into Sentinel would be for data retention needs beyond 30 days. \n   \n \n  Would there be any changes in the Microsoft Sentinel E5 benefit? \n \n There is no change in the existing Microsoft Sentinel E5 benefit. \n   \n \n Are there any changes in the default retention? \n \n No change in the default retention in the unified SOC platform. You will still be getting the 30 days of default retention for XDR data and 90 days for Microsoft Sentinel data at no additional retention cost. \n   \n Role Based Access Control (RBAC) \n \n What happens if the analyst has RBAC in place which filters Microsoft Defender XDR alerts, but has read access to the Microsoft Sentinel workspace? Will they see all the alerts, or the Microsoft Defender ones they have access to and all the Microsoft Sentinel ones? Or will they see all alerts regardless of the source? \n \n Since we unify two RBAC models: Azure/Sentinel RBAC and Defender RBAC, we apply a consolidated RBAC view to the unified portal incident queue, filtering out the service source(s) that they analyst is not allowed to see. \n However, if the analyst has Sentinel reader permissions, they still can access the SecurityIncident and SecurityAlert tables directly through Advanced Hunting or in Sentinel’s log search which contains the data that is filtered out in the unified portal. \n   \n For example, let's say a user has RBAC configured to view everything except for MDC alerts. The user won't be able to see the MDC alerts/incidents in the unified portal Also, if there is a multi-stage incident involving Sentinel, MDE, MDI and MDC alerts, the user can still see the incidents but not the individual MDC alerts that got correlated. However, take note that the user will be able to see the MDC alerts in Microsoft Sentinel portal since the user has read access to the workspace. \n   \n Copilot for Security in embedded experience \n 1. Do I need to purchase Microsoft Defender for Threat Intelligence (MDTI) license if I want to use the Copilot for Security embedded experience? \n No, if you have a Copilot for Security license, that should automatically include MDTI license. \n 2. Do I need another license for Copilot for Security? \n Yes, Copilot for Security is sold separately from SIEM and XDR. Find out more here Microsoft Copilot for Security - Pricing | Microsoft Azure. \n   \n Threat Intelligence \n \n With the unification, how should we be handling threat intel? Before we'd ingest it via the Security API for Microsoft Sentinel and Microsoft Defender, and then Microsoft Sentinel branched off into its own ingestion API. Are these being consolidated? (E.g. If you ingest threat intel into Microsoft Sentinel, can Microsoft Defender use it?) \n \n The Threat Intelligence experience remains the same and separated in the unified experience. However, we are considering making the experience more seamless. Stay tuned through our customer connection program for the latest updates. \n   \n UEBA \n \n Are there plans to consolidate UEBA components with unified platform? \n \n Entity pages for devices, users, IP addresses, and Azure resources in the Microsoft Defender portal display information from Microsoft Sentinel and Microsoft Defender data sources. These entity pages give you an expanded context for your investigations of incidents and alerts in the Defender portal. \n   \n Additional Resources \n \n Onboard Microsoft Sentinel to Microsoft Defender XDR \n Alerts, incidents, and correlation in Microsoft Defender XDR \n Advanced Hunting in Microsoft Defender XDR \n Automation in the unified security operation platform \n The unified security operations platform GA announcement \n Non-technical FAQ for Unified SOC platform  \n \n   \n Many thanks to my colleagues for reviewing and contributing to this article Tiander Turpijn \n AlexKlaus GBushey JeremyTan Sreedhar Ande  \n   \n   \n   \n   \n   \n   \n   \n   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Security Copilot Blog","shortTitle":"Microsoft Security Copilot Blog","parent":{"__ref":"Category:category:security-copilot"}},"User:user:1222825":{"__typename":"User","uid":1222825,"login":"jamilmirza","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/dS0xMjIyODI1LTQwMTk5MGkwMDNFMkExMDhGMzFFRDFG"},"id":"user:1222825"},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00NDA0NTYwLWxhZ1ptOA?revision=6\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00NDA0NTYwLWxhZ1ptOA?revision=6","title":"Create a an image which highlights Security Copilot and Logic Apps in a process diagram to highlight.jpeg","associationType":"COVER","width":1792,"height":1024,"altText":""},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00NDA0NTYwLXRZd3cyQQ?revision=6\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00NDA0NTYwLXRZd3cyQQ?revision=6","title":"clipboard_image-1-1744745053289.png","associationType":"BODY","width":601,"height":237,"altText":""},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00NDA0NTYwLXlod05Caw?revision=6\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00NDA0NTYwLXlod05Caw?revision=6","title":"Screenshot 2025-04-15 at 20.31.03.png","associationType":"BODY","width":692,"height":1380,"altText":""},"BlogTopicMessage:message:4404560":{"__typename":"BlogTopicMessage","subject":"Using Security Copilot to Proactively Identify and Prioritize Vulnerabilities","conversation":{"__ref":"Conversation:conversation:4404560"},"id":"message:4404560","revisionNum":6,"uid":4404560,"depth":0,"board":{"__ref":"Blog:board:SecurityCopilotBlog"},"author":{"__ref":"User:user:1222825"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"There are many ways to leverage the power of Security Copilot. In this blog we look at how we can use AI to help with alerting to vulnerabilities which need to be treated as a high priority.","metrics":{"__typename":"MessageMetrics","views":482},"postTime":"2025-04-16T10:04:19.992-07:00","lastPublishTime":"2025-04-16T10:04:19.992-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":"   \n Introduction  \n There are many different approaches when it comes to prioritizing the vulnerabilities which need addressing with urgency. Any information or guidance to help you make better informed decisions can be critical but how can you stay informed? Leveraging all the information sources available to you can be the difference and allow you to be proactive when trying to protect your organization.  \n  One useful feed is offered by CISA (Cybersecurity & Infrastructure Security Agency) who works with partners to defend against today’s threats and collaborate to build a more secure and resilient infrastructure for the future. The Known Exploited Vulnerabilities (KEV) Catalog is a curated list maintained by CISA. It identifies vulnerabilities that have been actively exploited in the wild, posing significant risks to organizations and individuals. The catalog aims to enhance cybersecurity by providing timely information on these vulnerabilities, enabling proactive mitigation efforts.  \n Key features of the KEV Catalog include:  \n \n Identification: Lists vulnerabilities that are confirmed to be exploited.  \n \n \n Details: Provides technical details, including affected products and versions.  \n \n \n Mitigation: Offers guidance on how to address and remediate the vulnerabilities.  \n \n \n Updates: Regularly updated to reflect new threats and exploited vulnerabilities.  \n \n The KEV Catalog serves as a critical resource for cybersecurity professionals, helping them prioritize patching and defense strategies to protect against known threats. \n The feed is designed to help organizations stay informed about vulnerabilities that have been exploited in the wild. It is part of CISA's efforts to defend against current threats and build a more secure and resilient infrastructure for the future  \n Workflow overview  \n The automated CISA feed solution addresses prioritization challenges by streamlining the process of vulnerability management. This solution checks the latest CISA feed every 24 hours and queries the CVE findings against devices within Microsoft Defender for Endpoint. Security Copilot then checks for remediation actions and enriches the description, providing a comprehensive overview of the vulnerability.  \n   \n \n Key benefits of the Logic App include:  \n \n Automated Updates: The Logic App automatically retrieves the latest CISA feed, ensuring that analysts have up-to-date information without manual intervention. This eliminates the need for manual checks and reduces the risk of missing critical updates.  \n \n \n Device Vulnerability Assessment: It queries the CVE findings against devices within the organization, identifying which devices are vulnerable to the reported CVEs. This targeted approach allows analysts to focus on the most critical vulnerabilities affecting their specific environment, enhancing the efficiency of the remediation process.  \n \n \n Remediation Insights: Security Copilot provides detailed remediation actions, helping analysts understand the steps needed to mitigate the vulnerabilities. By enriching the description with actionable insights, it simplifies the decision-making process and accelerates the implementation of security measures.  \n \n \n Email Notifications: An email with the findings is sent to a designated mailbox, allowing for easy review and follow-up. This ensures that all relevant stakeholders are informed promptly, facilitating coordinated responses and continuous monitoring of the organization's security posture.  \n \n \n Click here to get started and install the Logic App today.  \n Conclusion  \n To prioritize effectively, gather all necessary information for informed decisions. While the Logic App CISA workflow is one approach, other methods may better suit your organization. Function Apps can enhance decision making by automating and streamlining security operations with integrated tools and processes. The Security Copilot GitHub repository offers AI-powered solutions using machine learning and natural language processing to improve security. These tools help identify vulnerabilities, predict risks, and implement protective measures. Check it out! 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Copilot","conversation":{"__ref":"Conversation:conversation:4402551"},"id":"message:4402551","revisionNum":2,"uid":4402551,"depth":0,"board":{"__ref":"Blog:board:SecurityCopilotBlog"},"author":{"__ref":"User:user:114736"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" By leveraging Microsoft Entra ID Application Proxy and Azure Application Gateway with Web Application Firewall (WAF), you can securely connect on-premises or self-hosted Splunk instances to Microsoft Security Copilot—enabling seamless log analysis and threat investigation without exposing Splunk to the internet. This approach extends Security Copilot’s reach beyond SaaS applications, broadening the context needed for effective investigations across hybrid environments. ","introduction":"Microsoft Security Copilot is a SaaS-based, AI-powered cybersecurity solution that uses generative AI to empower defenders to protect at speed and scale of AI. Integrating Security Copilot with other SaaS platforms is generally straightforward thanks to native cloud-to-cloud connectivity. This includes native cloud-to-cloud integration with Splunk Cloud, now part of Cisco.\nThe Security Copilot plugin for Splunk also supports on-premises and self-hosted VM deployments of Splunk; however, additional steps are required to enable secure and reliable communication in these scenarios.","metrics":{"__typename":"MessageMetrics","views":414},"postTime":"2025-04-10T08:30:00.016-07:00","lastPublishTime":"2025-04-10T08:30:00.016-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Microsoft Security Copilot is a SaaS-based, AI-powered cybersecurity solution that uses generative AI to empower defenders to protect at speed and scale of AI. Integrating Security Copilot with other SaaS platforms is generally straightforward thanks to native cloud-to-cloud connectivity. This includes native cloud-to-cloud integration with Splunk Cloud, now part of Cisco. \n The Security Copilot plugin for Splunk also supports on-premises and self-hosted VM deployments of Splunk; however, additional steps are required to enable secure and reliable communication in these scenarios. \n This blog walks you through how to integrate Security Copilot with non-SaaS editions of Splunk using Microsoft Entra ID Application Proxy and Azure Application Gateway with Web Application Firewall (WAF). This setup ensures that your Splunk instance remains protected behind enterprise-grade security controls while still being accessible to Security Copilot for log analysis and threat investigation. \n While this guidance is specifically for Splunk the same general principles can be applied to integrate other on-prem solutions with Security Copilot. \n Solution overview \n In this blog post, we illustrate how to securely integrate Microsoft Security Copilot with Splunk in two common scenarios: \n \n When your Splunk instance is already running within an Azure Virtual Network (VNet). \n When your Splunk instance is deployed on-premises but you already have network connectivity to an Azure VNet through VPN or ExpressRoute. \n \n If these conditions are not met—for example, if your Splunk deployment is fully isolated on-premises without connectivity to Azure—it is still possible to securely expose your instance to Security Copilot by using a reverse proxy hosted on-premises instead of Azure Application Gateway. However, that approach is outside the scope of this blog. \n   \n The solution presented here relies on a combination of Microsoft Entra ID Application Proxy and Azure Application Gateway with Web Application Firewall (WAF) to create a secure, controlled communication channel between Security Copilot and your Splunk instance. \n Entra ID Application Proxy is used to publish the Splunk REST endpoint in a secure manner. This ensures that the Splunk instance is not directly exposed to the Internet and that no inbound ports need to be opened on your firewall. \n Azure Application Gateway, equipped with WAF, acts as a reverse proxy that enforces access controls based on source IP addresses. It ensures that only traffic originating from the known Security Copilot egress IPs is allowed to reach the published Splunk endpoint. Additionally, WAF allows you to enforce protections such as the OWASP Top 10, Bot Protection and custom rules adding another layer of defense. \n This approach is applicable not only for Splunk instances hosted in Azure, but also for self-hosted VM deployments running on other public clouds such as AWS or GCP, as long as they are reachable via a secure VNet-integrated path. \n Below is a high-level view of the architecture: \n \n Step by step deployment guide \n The following sections describe the procedures for configuring Microsoft Entra ID Application Proxy and Azure Application Gateway to enable secure integration between Security Copilot and your Splunk instance. \n ⚠️ Important: While the guidance provided outlines a reference architecture, please make sure to adapt all configuration steps to reflect your actual network topology and IP address space. Specific settings such as subnet ranges, routing paths, and firewall rules should align with your organization’s infrastructure design and security policies. \n Entra ID Application Proxy setup and configuration \n Download and Configure the Connector Service \n To enable secure connectivity between Security Copilot and your on-premises or self-hosted Splunk instance, begin by setting up the Entra ID Application Proxy connector: \n \n Download the connector from the Azure Portal: go to https://portal.azure.com → Entra ID → Application Proxy. \n \n \n \n Ensure your network environment is properly configured for outbound connectivity. Refer to Microsoft's documentation for detailed prerequisites and firewall rules. \n The connector must be installed on a Windows Server 2012 R2 or later. \n Once installed successfully, the connector establishes a secure outbound communication channel with Azure. You can verify its status under the Health Status section in the portal. \n \n   \n \n Configure an Entra ID Application for Splunk \n The next step is to publish your Splunk instance as an app via Application Proxy. This allows Security Copilot to securely invoke Splunk’s APIs, which are exposed on the default management port 8089. \n Note: Ensure that the splunkd service is configured with a valid SSL certificate. The connector requires HTTPS for communication. \n \n In the Application Proxy section, click on “Configure an app”. \n \n   \n \n   \n \n Fill in the relevant fields. Under the Pre-authentication section, select \"Passthrough\". Since the Security Copilot plugin supports either API Key Authentication or Basic Authentication, it cannot perform Microsoft Entra ID authentication. Therefore, authentication must be handled directly by Splunk. \n \n   \n \n Important: To add an additional security layer and restrict access only to Security Copilot’s egress IP addresses, a custom WAF Policy will be configured on the Application Gateway, as described in the following section. \n \n Once configured, the app will be visible under Entra ID → App registrations. \n \n \n   \n \n You can test the application by navigating to the external URL defined during setup. \n \n Note: Although Splunk listens on port 8089, Application Proxy exposes the service externally over port 443 (HTTPS). \n Licensing Requirement: Entra ID P1 licenses or higher are required to use Application Proxy. \n Application Gateway and WAF Configuration \n You can use the Azure Portal wizard to create and configure the Application Gateway with the following steps: \n Tip: If you already have Azure DDoS deployed and can use the same Virtual Network there will be no additional charges to the WAF as detailed here: Azure DDoS Protection frequently asked questions | Microsoft Learn \n \n Create the Application Gateway \n \n \n Navigate to Create a resource > Networking > Application Gateway. \n Select the appropriate Resource Group and Azure region. \n For Tier, choose WAF V2. \n If you already have a WAF Policy, select it. Otherwise, you can create one later using the configuration guidance provided in the next section. \n Choose the dedicated subnet (e.g., subnet-appgw) for the Application Gateway instance. \n \n   \n \n   \n \n Configure the Frontend IP \n \n \n Select Private as the frontend IP type. \n Assign a static private IP address from the selected subnet. This IP will serve as the entry point for requests coming from Entra ID Application Proxy. \n \n \n \n Add the Backend Pool \n \n \n Add your Splunk Search Head as a backend target. \n This can be either:\n \n A VM running in the same VNet as AppGW, or \n A Splunk instance hosted on-premises, reachable via VPN or ExpressRoute. \n \n \n \n \n \n Configure Routing Rules \n \n \n Under the Configuration tab, add a Routing Rule:\n \n Create a Listener and bind it to the private frontend IP you configured in step 2. \n Upload your Splunk instance’s TLS certificate in PFX format to enable HTTPS. \n Set the backend protocol to HTTPS and the port to 8089, which is the default for Splunk’s management and search APIs. \n \n \n \n \n   \n \n   \n \n Tags (optional) \n \n \n Add tags as needed for resource classification, billing, or automation purposes. \n \n \n Review and Create \n \n \n Review your configuration and create the Application Gateway. \n \n   \n \n Once deployed, the Application Gateway will serve as a secure intermediary, ensuring that only requests from the known Security Copilot egress IPs reach your Splunk instance, and that all communication is encrypted and inspected by WAF. \n WAF Policy configuration \n Create a WAF Policy, associate it with the Application Gateway, and configure a custom rule as follows to allow traffic only from the Security Copilot egress IPs. Note: Since the traffic is proxied through Entra ID Application Proxy, the source IP check must be performed on the X-Forwarded-For header. \n   \n \n Configuring your Splunk plugin in Security Copilot \n \n Navigate to the Splunk plugin and select Setup \n \n   \n \n   \n \n Choose your preferred authentication method (API Key) recommended \n \n \n \n Enter the external url generated by Entra ID App proxy and click save \n \n \n Conclusion \n By leveraging Microsoft Entra ID Application Proxy and Azure Application Gateway with Web Application Firewall (WAF), you can securely connect on-premises or self-hosted Splunk instances to Microsoft Security Copilot - enabling seamless log analysis and threat investigation without exposing Splunk to the internet. This approach extends Security Copilot’s reach beyond SaaS applications, broadening the context needed for effective investigations across hybrid environments. \n Additional resources \n Splunk and Microsoft Security Copilot | Microsoft Learn \n Deploy Microsoft Entra application proxy for Microsoft Entra Domain Services - Microsoft Entra ID | Microsoft Learn \n Plan a Microsoft Entra application proxy Deployment - Microsoft Entra ID | Microsoft Learn \n Using Application Gateway WAF to protect your application - Microsoft Entra ID | Microsoft Learn \n Web application firewall exclusion lists in Azure Application Gateway - Azure portal | Microsoft Learn \n Network topology considerations for Microsoft Entra application proxy - Microsoft Entra ID | Microsoft Learn \n Tutorial - Create S2S VPN connection between on-premises network and Azure virtual network: Azure portal - Azure VPN Gateway | Microsoft Learn 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Microsoft Graph as a Microsoft Copilot for Security Plugin with Delegated Access","conversation":{"__ref":"Conversation:conversation:4198148"},"id":"message:4198148","revisionNum":9,"uid":4198148,"depth":0,"board":{"__ref":"Blog:board:SecurityCopilotBlog"},"author":{"__ref":"User:user:2274421"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" In this article, we show how to build a Copilot for Security API plugins that call Microsoft Graph APIs using delegated access. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":5882},"postTime":"2024-07-24T09:09:51.617-07:00","lastPublishTime":"2025-02-03T09:49:36.489-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Microsoft Graph offers a powerful and flexible way to retrieve data from several Microsoft products.  Using well documented REST APIs you can pull data from diverse sources like security incidents, SharePoint documents, emails, Teams chat among several others. All Graph API calls support the OData specification and return data in JSON format. OData URL specification allow REST calls to include select, filter and other clauses all of which give control to the amount of data we want the API response to include. \n   \n Microsoft Copilot for Security (Copilot) is a large language model (LLM) based generative Artificial Intelligence (AI) system for cybersecurity use cases. Copilot is not a monolithic system but is an ecosystem running on a platform that allows data requests from multiple sources using a unique plugin mechanism. The plugin mechanism gives Copilot the capability to pull data for any external data source as long as it supports REST API, thus allowing Copilot to make Graph APIs calls. \n   \n This article assumes familiarity with Microsoft Graph, Copilot and usage of REST APIs, and is intended as a generic example on calling Graph APIs from Copilot.  \n   \n Microsoft Graph \n Microsoft’s Graph offers a single endpoint (https://graph.microsoft.com), to provide access to rich, data and insights from several sources the Microsoft cloud, including Microsoft 365, Windows, and Enterprise Mobility + Security. If you have not worked with Microsoft Graph API before, the best place to start is its main document page available here. \n   \n Like with any other REST API, it is good to use a REST API client (Boomerang, Postman etc.) to experiment and test the API. With Microsoft Graph there is another option called Graph Explorer to evaluate all the APIs. Using Graph Explorer is much faster and convenient than using other REST clients as it handles getting authentication tokens and is also directly linked with the Graph documentation.  When you go to Graph Explorer from this link, the main page comes up as shown below: \n   \n   \n Once in Graph Explorer, you will be asked to authenticate with your Microsoft tenant credentials. While this is not required to make API calls, it is strongly recommended as after authentication Graph Explorer will retrieve the JSON Web Token (JWT) for your account which is required as a Bearer token in the header in each Graph API call. JWT will also allow Graph Explorer to retrieve data from your tenant (as compared to generic data shown when not authenticated). \n      \n Permissions \n Each Graph API call requires that your account (and the JWT) have the required permissions to see the data, more details on Graph permissions are given here.  Since Graph Explorer is acting on behalf of the authenticated user, this is termed ‘on behalf of’ authentication with delegated access. The delegated permissions are also called scopes and are contained within the JWT. If you do not have the required permissions, the REST call will return with an ‘Unauthorized’ (HTTP 401) error.  For each Graph call, under the ‘Modify permissions’ tab Graph Explorer shows one or more of the permissions needed by the call as shown below: \n   \n Depending on your role and permissions assignment in Entra, you can consent to one of the permissions required to make the call. The JWT scope should contain the permissions that allow Graph Explorer or any other application acting on behalf of the user, to successfully retrieve the data required from the call. You can see the content of a JWT and the scope it contains from the jwt.ms website. \n   \n Let us define a use case based on which we will decide the Graph APIs to call and then build a Copilot API plugin for it. Before building a Copilot plugin that uses Graph API, make sure you have looked at all the skills present in the several Microsoft () plugins available out-of-the-box in Copilot. New Microsoft plugins and additional skills to existing plugins are constantly being added and this will ensure you are not building a plugin for a functionality that already exists. For our use case we will build a plugin to extract all Alert IDs from an incident and then based on the Alert ID it will allow us to pull the evidence associated with that alert. \n   \n Head to Graph Explorer console, authenticate and go to the Security group in the left navigation bar. Selecting the ‘alerts’ option will update the URL in the right pane. If the URL does not point to the new unified Microsoft 365 Alerts and Incident API (ends in ‘alert’ and not ‘alert_v2’), change the URL to end in ‘alert_v2’. \n   \n Since it is based on the OData specification, Graph API supports several selection criterion and filter options that narrow the scope of the data being returned. For a Copilot for Security plugin this is very important as use of selection and filters criterion reduces the size of the data being returned by the API allowing Copilot to process it more efficiently. These options are passed as query parameters in the URL and detailed description of supported options are available in the Microsoft Graph documentation here. Note that if the data field your need is not available in the JSON returned from the Graph API call, then it is an advanced use case not covered by this article. In these cases, you will have to modify/massage the data using Logic Apps, Azure Functions or Webservice and then integrate with Copilot. \n   \n In our first API call, we will use the $count option that will insert a count field in the output JSON. The $count option is added as query parameter as shown in the screen capture below. Once you press the ‘Run Query’ button Graph Explorer will make the REST API call, the output/response JSON of which is shown in the ‘Response preview’ pane. Note the field ‘@data.count’ that is added by the $count query parameter which shows the number of returned alerts: \n   \n   \n Our use case calls for looking at alerts only in a specific incident. Though the returned JSON has a field ‘incidentId’ showing the Incident ID each alert belongs to, there are too many alerts that are not useful. Our goal is to return as minimum data to Copilot as possible, so we will use a Odata filter to narrow down the incident and get alerts assigned to it. \n   \n A filter is added using the $filter query parameter and its value is set to ‘incidentId eq '15'’ that tells Microsoft Graph to only return alerts whose ‘incidentId’ is 15. The output of this call is shown below: \n   \n   \n We can see that after adding the filter only 2 alerts are returned. After cross refencing incident 15 in the unified Defender console, the returned information is correct: \n   \n   \n Though we have the required alerts, we are still pulling in data fields that are not useful for our use case (we only need alert ids along with their description). To narrow down the fields, we will use the $select query parameter and set its value to ‘id,title’ making the combined URL: https://graph.microsoft.com/v1.0/security/alerts_v2?$filter=incidentID  eq '15'&$count=true&$select=id,title \n   \n Making this API request, gives us the exact date we need as show in the ‘Response preview’: \n   \n   \n   \n Copilot API Plugin \n We are now ready to define the YAML files required to have Copilot make the Graph API call. The main YAML file is given below, for more details on these YAML files and their field refer to this article: \n   \n   \n Descriptor:\n Name: Defender Specific Alert Details Plugin\n DisplayName: Defender Specific Alert Details Plugin\n Description: The skills in this plugin will help get Defender alert details via Graph API Call\n DescriptionForModel: The skills in this plugin will help get specific defender alert details based on provided incident or alert id.\n\n SupportedAuthTypes:\n - AADDelegated\n Authorization:\n Type: AADDelegated\n EntraScopes: https://graph.microsoft.com/.default\n\nSkillGroups:\n - Format: API\n Settings:\n OpenApiSpecUrl: http://<URL for OpenAPI File>/API_Plugin_GraphAPI_Alerts_OAI.yaml \n   \n   \n Authentication \n Note the value for ‘SupportedAuthTypes’ and ‘Authorization’ defined as ‘AADDelegated’ (Azure Active Directory Delegated). When Authorization is set to ‘AADDelegated’ you tell Copilot to use delegated access (or ‘act on behalf’) of the user who is logged into Copilot, when making the Graph API call. This way Copilot makes it very easy to make Graph API calls, and does not require you having to go to the Microsoft Entra Admin Center and register your application as described here. . For that, we have to use OAuth2 and get an application ID by registering an application and this will be discussed in a follow-on article. Along with ‘AADDelegated’ Copilot supports OAuth2 authentication along with several other listed here: \n   \n With the important discussion on authentication out of our way, let us see the second YAML file which is for the OpenAPI specification for our Plugin: \n   \n   \n openapi: 3.0.0\n\ninfo:\n title: Defender Specific Alert Details Plugin\n description: Skills for getting alert details via Graph API Call\n version: \"v1\"\nservers:\n - url: https://graph.microsoft.com/v1.0/security\n\npaths:\n /alerts_v2?$select=id,title:\n get:\n operationId: GetAlertIdsFromIncidentId\n description: List all alert id's based on a user provided incident id\n ExamplePrompt:\n - 'show me alert ids for the specified incident id'\n - 'Get me all alert ids where incident id is provided'\n parameters:\n - in: query\n name: $filter\n schema:\n type: string\n required: true\n description: A filter in the format of \"incidentid eq id\" where ID is an incident ID provided by the user.\n responses:\n \"200\":\n description: OK\n content:\n application/json: \n   \n   \n After placing the OpenAPI definition YAML in an Internet accessible URL, we go to the Copilot console and follow the steps to import the custom plugin: \n   \n   \n Once the plugin is imported it will show under the custom plugin area, make sure it has been enabled. \n   \n We will now invoke our newly imported plugin’s skill directly to verify that it is able to make a successful call and fetch the data. To invoke a skill directly, click on the prompt icon as shown below: \n   \n   \n Select, the ‘See all system capabilities’ link and then search for Alert: \n   \n   \n This will show the operationId and Description of the skill. Our plugin has only one skill so far (GetAlertIdsFromIncidentId) so we will select it: \n   \n   \n and pass it the value of the filter: \n   \n   \n If the call is successful, Copilot will complete all the 3 steps and show the response: \n   \n   \n After verification with the earlier call in Graph Explorer the Alerts ids and their descriptions look correct and belong to Incident 15. \n You can also invoke a skill directly from the Copilot command window using the ‘/’ command as shown below. This gives the same result as before, confirming that Copilot can successfully make the Graph API call, pass the correct credentials for Delegated access and fetch the data. \n   \n Note that if you get a permission denied error, check with your Azure admin if you have the requires roles/permissions to read security related information. \n   \n Getting Evidence based on Alert Ids \n Now that we have the alerts ids, let us now expand our plugin’s capability to get evidence details about a specific alert. The following Graph API URL: https://graph.microsoft.com/v1.0/security/alerts_v2/{alertid}    \n   \n will fetch information specific to the ‘alertid’ passed to it. In Graph Explorer, the ‘Response preview’ of this API for alert id ‘fab098dd19-bcbd-61e1-7eb2-08dc96ce5a71’ (part of Incident 15) is shown below: \n   \n   \n The call returns a lot of data attributes but as per our use case we are only interested in evidence related data. To only have data related to the evidence information, \n https://graph.microsoft.com/v1.0/security/alerts_v2/{alertid}?$select=evidence    \n   \n The Response preview for the updated URL call is shown below: \n   \n   \n Now we need to have this capability added to our plugin. The main YAML file will remain the same but the OpenAPI specification will change to support one more REST API. The updated YAML file is given below: \n   \n   \n   \n   \n openapi: 3.0.0\n\ninfo:\n title: Defender Specific Alert Details Plugin\n description: Skills for getting alert details via Graph API Call\n version: \"v1\"\n\nservers:\n - url: https://graph.microsoft.com/v1.0/security\n\npaths:\n /alerts_v2?$select=id,title:\n get:\n operationId: GetAlertIdsFromIncidentId\n description: List all alert id's based on a user provided incident id\n ExamplePrompt:\n - 'show me alert ids for the specified incident id'\n - 'Get me all alert ids where incident id is provided'\n parameters:\n - in: query\n name: $filter\n schema:\n type: string\n required: true\n description: A filter in the format of \"incidentid eq id\" where ID is an incident ID provided by the user.\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n\n # New API added\n /alerts_v2/{alertid}?$select=evidence:\n get:\n operationId: GetEvidenceForSpecificAlert\n description: Get all the evidence details of a specific alert id\n parameters:\n - in: path\n name: alertid\n schema:\n type: string\n required: true\n description: id of the alert\n responses:\n \"200\":\n description: OK\n content:\n application/json: \n   \n   \n   \n   \n Note that that $select query parameter is hard-coded but the alert before it is taken a path input. OpenAPI specifications allow fixed query parameters after variable fields which is nice and helps us here. \n   \n After re-importing (delete old plugin and import again) the updated plugin, let us invoke the skill directly as we have done before with the same alert id. First search by the Alert, and now we will see two skills for our plugin: \n   \n   \n Select ‘GetEvidenceForSpecificAlert’ and enter the alert id: \n   \n Copilot makes a successful call and neatly summaries each of the evidence items: \n   \n   \n The evidence API call pulls in several evidence objects, and if you need to see data only in a specific evidence, Copilot will need to be prompted to do the filtering once the data is received from the API call. The following prompt will show details of only the Analyzed Message Evidence: \n   \n “Get evidence for specific alert with id fab098dd19-bcbd-61e1-7eb2-08dc96ce5a71 and show the details contained in the Analyzed Message Evidence”: \n   \n   \n In this article, we have shown how straightforward it is to build a Copilot for Security plugin that makes Graph API calls. We used Copilot’s ‘AADDelegated’ authentication type which allows us to make Graph API calls with delegated access. In a follow up article, we will look at making Graph API calls from Copilot with OAuth2 authentication. \n   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Flight with Microsoft Security Copilot Flight School","conversation":{"__ref":"Conversation:conversation:4391712"},"id":"message:4391712","revisionNum":4,"uid":4391712,"depth":0,"board":{"__ref":"Blog:board:SecurityCopilotBlog"},"author":{"__ref":"User:user:2229415"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":1085},"postTime":"2025-03-12T08:00:00.019-07:00","lastPublishTime":"2025-03-13T18:20:14.508-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Greetings pilots, and welcome to another pioneering year of AI innovation with Security Copilot. Find out how your organization can reach new heights with Security Copilot through the many exciting announcements on the way at both Microsoft Secure and RSA 2025. This is why now is the time to familiarize yourself and get airborne with Security Copilot. \n Go to School \n Microsoft Security Copilot Flight School is a comprehensive series charted to take students through fundamental concepts of AI definitions and architectures, take flight with prompting and automation, and hit supersonic speeds with Logic Apps and custom plugins. By the end of the course, students should be equipped with the requisite knowledge for how to successfully operate Security Copilot to best meet their organizational needs. The series contains 11 episodes with each having a flight time of around 10 minutes.   \n Security Copilot is something I really, really enjoy, whether I’m actively contributing to its improvement or advocating for the platform’s use across security and IT workflows. Ever since I was granted access two years ago – which feels like a millennium in the age of AI – it’s been a passion of mine, and it’s why just recently I officially joined the Security Copilot product team. This series in many ways reflects not only my passion but similar passion found in my marketing colleagues Kathleen Lavallee (Senior Product Marketing Manager, Security Copilot) Shirleyse Haley (Senior Security Skilling Manager), and Shateva Long (Product Manager, Security Copilot). I hope that you enjoy it just as much as we did making it. \n Go ahead, and put on your favorite noise-cancelling headphones, it’s time, pilots, to take flight. \n Log Flight Hours \n There are two options for watching Security Copilot Flight School: either on Microsoft Learn or via the Youtube Playlist found on the Microsoft Security Youtube Channel. The first two episodes focus on establishing core fundamentals of Security Copilot platform design and architecture – or perhaps attaining your instrument rating. The episodes thereafter are plotted differently, around a standard operating procedure. To follow the ideal flight path Security Copilot should be configured and ready to go – head over to MS Learn and the Adoption Hub to get airborne. It’s also recommended that pilots watch the series sequentially, and be prepared to follow along with resources found on Github, to maximize learning and best align with the material. This will mean that you’ll need to coordinate with a pilot with owner permissions for your instance to create and manipulate the necessary resources.  \n   \n Episode 1 - What is Microsoft Security Copilot? \n \n Security is complex and requires highly specialized skills to face the challenges of today. Because of this, many of the people working to protect an organization work in silos that can be isolated from other business functions. Further, enterprises are highly fragmented environments with esoteric systems, data, and processes. All of which takes a tremendous amount of time, energy, and effort just to do the day-to-day. \n Security Copilot is a cloud-based, AI-powered security platform that is designed to address the challenges presented by complex and fragmented enterprise environments by redefining what security is and how security gets done. \n What is AI, and why exactly should it be used in a cybersecurity context? \n   \n Episode 2 - AI Orchestration with Microsoft Security Copilot \n \n Why is The Paper Clip Pantry a 5-star restaurant renowned the world over for its Wisconsin Butter Burgers?  Perhaps it’s how a chef uses a staff with unique skills and orchestrates the sourcing of resources in real time, against specific contexts to complete an order. After watching this episode you’ll understand how AI Orchestration works, why nobody eats a burger with only ketchup, and how the Paper Clip Pantry operates just like the Security Copilot Orchestrator. \n   \n Episode 3 – Standalone and Embedded Experiences \n \n Do you have a friend who eats pizza in an inconceivable way? Maybe they eat a slice crust-first, or dip it into a sauce you never thought compatible with pizza? They work with pizza differently, just like any one security workflow could be different from one task, team, or individual to the next. This philosophy is why Security Copilot has two experiences – solutions embedded within products, and a standalone portal – to augment workflows no matter their current state. This episode will begin covering those experiences. \n   \n Episode 4 – Other Embedded Experiences \n \n Turns out you can also insist upon putting cheese inside of pizza crust, or bake it thick enough as to require a fork and knife. I imagine, it’s probably something Windows 95 Man would do. \n In this episode, the Microsoft Entra, Purview, Intune, and Microsoft Threat Intelligence products showcase how Security Copilot advances their workflows within their portals.  Beyond baking in the concepts of many workflows, many operators, the takeaway from this episode is that Security Copilot works with security adjacent workflows – IT, Identity, and DLP. \n Episode 5 – Manage Your Plugins \n \n Like our chef in The Paper Clip Pantry, we should probably define what we want to cook, what chefs to use, and set permissions for those that can interact within any input or output from the kitchen.  Find out what plugins add to Security Copilot and how you can set plugin controls for your team and organization. \n Episode 6 – Prompting \n \n Is this an improv lesson, or a baking show? Or maybe if you watch this episode, you’ll learn how Security Copilot handles natural language inputs to provide you meaningful answers know as responses. \n Episode 7 – Prompt Engineering \n response, consider your goal, the context needed, sources available, and the final presentation of the information to achieve the best result.\n With the fundamentals of prompting in your flight log, it’s time to soar a bit higher with prompt engineering.  In this episode you will learn how to structure prompts in a way to maximize the benefits of Security Copilot and begin building workflows.  Congrats, pilot, your burgers will no longer come with just ketchup. \n Episode 8 – Using Promptbooks \n \n What would it look like to find a series of prompts and run them, in the same sequence with the same output every time? You guessed it, a promptbook, a repeatable workflow in the age of AI.  See where to access promptbooks within the platform, and claw back some of your day to perfect your next butter burger. \n Episode 9 – Custom Promptbooks \n \n You’ve been tweaking your butter burger recipe for months now.  You’ve finally landed at the perfect version by incorporating a secret nacho cheese recipe. The steps are defined, the recipe perfect. How do you repeat it? \n Just like your butter burger creation, you might discover or design workflows with Security Copilot. With custom promptbooks you can repeat and share them across your organization.  In this episode you’ll learn about the different ways Security Copilot helps you develop your own custom AI workflows. \n Episode 10 – Logic Apps \n \n System automation, robot chefs? Actions?  What if customers could order butter burgers with the click of a button, and the kitchen staff would automatically make one? Or perhaps every Friday at 2pm a butter burger was just delivered to you?  Chances are there are different conditions across your organization that when present requires a workflow to begin. With Logic Apps, Security Copilot can be used to automatically aid workflows across any system a Logic App can connect to.  More automation, less mouse clicking, that’s a flight plan everyone can agree on. \n   \n Episode 11 – Extending to Your Ecosystem \n \n A famed restaurant critic stopped into the The Paper Clip Pantry ordered a butter burger, and it’s now the burger everyone is talking about. Business is booming and it's time to expand the menu – maybe a butter burger pizza, perhaps a doughnut butter burger? But you’ll need some new recipes and sources of knowledge to achieve this.    Like a food menu the possibilities of expanding Security Copilot’s capabilities are endless.  In this episode learn how this can be achieved with custom plugins and knowledgebases. Once you have that in your log, you will be a certified Ace, and ready to take flight with Security Copilot. \n Take Flight \n I really hope that you not only learn something new but have fun taking flight with the Security Copilot Flight School. As with any new and innovative technology, the learning never stops, and there will be opportunities to log more flight hours from our expert flight crews.  Stay tuned at the Microsoft Security Copilot video hub, Microsoft Secure, and RSA 2025 for more content in the next few months.  \n If you think it’s time to get the rest of your team and/or organization airborne there’s check out the Security Copilot adoption hub to get started: \n aka.ms/SecurityCopilotAdoptionHub \n Carry-on Resources \n Our teams have been hard at work building solutions to extend Security Copilot, you can find them on our community Github page found at: \n aka.ms/SecurityCopilotGitHubRepo \n   \n To stay close to the latest in product news, development, and to interact with our engineering teams, please join the Security Copilot CCP to get the latest information:  \n aka.ms/JoinCCP 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Security Copilot with NL2KQL: Transforming Natural Language into Insightful KQL queries","conversation":{"__ref":"Conversation:conversation:4388930"},"id":"message:4388930","revisionNum":9,"uid":4388930,"depth":0,"board":{"__ref":"Blog:board:SecurityCopilotBlog"},"author":{"__ref":"User:user:814378"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" By leveraging NL2KQL, a powerful framework that translates natural language into KQL queries, Security Copilot makes querying in KQL as intuitive as a conversation. In this article, we’ll explore the story behind NL2KQL, its potential to transform security operations, and why it matters for the future of cybersecurity. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":1206},"postTime":"2025-03-04T09:59:10.727-08:00","lastPublishTime":"2025-03-07T09:53:11.311-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Imagine being at the forefront of a dynamic Security Operations Center (SOC), managing and analyzing millions of daily event logs. You're hunting for clues—perhaps unauthorized remote logins from a suspicious IP range—but translating that intent into a corresponding Kusto Query Language (KQL) query isn't always straightforward. \n KQL is the powerhouse behind services like Microsoft Sentinel and Microsoft Defender, enabling security professionals to query and analyze vast amounts of data effectively. However, KQL comes with challenges: it requires precise syntax, detailed knowledge of table schemas, and an understanding of functions and grouping. For many security analysts, this learning curve can slow down threat investigation and response. \n With Microsoft Security Copilot, an enterprise-grade AI assistant powered by GPT, that vision has become a reality. By leveraging NL2KQL, a framework that translates natural language into corresponding KQL queries, Security Copilot makes querying in KQL as intuitive as a conversation. In this article, we’ll explore the story behind NL2KQL, its potential to transform security operations, and why it matters for the future of cybersecurity. \n The Problem: A Communication Barrier Between Analysts and Data \n In the high-stakes environment of a SOC, time is critical. Yet, analysts often face a dual challenge: understanding the nuances of evolving threats while mastering the tools and languages required to analyze them. KQL, while powerful, is unforgiving of errors—a misplaced parenthesis or an incorrect function can lead to failed queries or inaccurate results. Additionally, KQL lacks features common in relational databases, such as primary or foreign keys, making it even more challenging for analysts to navigate unfamiliar data schemas. \n This creates a communication barrier. Analysts think in terms of security scenarios (“I want to identify failed login attempts from this IP range”), but translating those scenarios into syntactically correct KQL commands requires time, effort, and expertise. \n The NL2KQL Solution Within Microsoft Security Copilot \n \n NL2KQL was designed to let security analysts communicate with data “as they are”—in natural language—while our system handles the translation into corresponding KQL commands. Leveraging the capabilities of large language models (LLMs), NL2KQL interprets an analyst’s natural language query (NLQ), understands its intent, and generates corresponding KQL commands. The pipeline includes the following key components: \n \n Semantic Data Catalog: A core component of NL2KQL is the semantic data catalog, encapsulating information about the structure, semantics, and contextual attributes of the database. This catalog includes annotations for tables, columns, type constraints, and enumerated values where applicable. Embeddings of table elements, column elements, and value elements are calculated using a similarity embedding model and stored in a vector database for quick retrieval during inference. \n Schema Refiner: Generating semantically valid KQL requires an relevant schema representation. The Schema Refiner dynamically selects the most relevant tables, columns, and potential values from the semantic data catalog to include in the model’s context. This approach addresses constraints such as limited context window sizes and varying user permissions. \n Few-Shot Selector: A synthetic few-shot database guides the LLM. The Few-Shot Selector dynamically identifies relevant examples based on the user’s NLQ and schema context. By leveraging precomputed embeddings stored in a vector database, the selector retrieves and ranks few shots using cosine similarity. \n Prompt Builder: Crafting an effective prompt is key to LLM performance. NL2KQL’s prompt integrates instructions, relevant schema details from the Schema Refiner, selected few-shots, essential Kusto syntax elements, and best practices for query optimization. This comprehensive context ensures efficient query generation. \n Query Refiner: The Query Refiner validates and repairs the generated KQL to ensure syntactic and semantic correctness. By leveraging the official KQL parser library, it identifies errors, handles undefined variables, fixes joins, and adds missing operators. This recursive process ensures reliable outputs even for complex queries. \n \n Real-World Scenarios: NL2KQL in Security Copilot \n In Microsoft Defender XDR \n Microsoft Security Copilot in Microsoft Defender XDR comes with a query assistant capability in advanced hunting. By clicking the \"generate query\" button, threat hunters or security analysts can ask a question in natural language, and NL2KQL then generates a corresponding KQL query that corresponds to the request using the advanced hunting data schema. This query can be easily copied for further refinement or executed directly in the advanced hunting query pane—accelerating investigations and reducing manual effort. For more details on this feature, please visit Microsoft Security Copilot in advanced hunting - Microsoft Defender XDR \n \n In the Standalone Security Copilot Experience \n In the standalone Security Copilot interface, after you pose a natural language query, NL2KQL generates a corresponding KQL query and presents it for your review. Users have the option to enable Security Copilot to also execute the query and display the results. However, it's essential to note that while the system is designed to produce corresponding queries, the output may not always be perfect. It's important to review the generated query to ensure it meets your requirements. \n \n Note: You can prompt Security Copilot to generate advanced hunting queries for both Defender XDR and Microsoft Sentinel tables. Not all Microsoft Sentinel tables are currently supported, but support for these tables can be expected in the future. \n Why This Matters in the Security Domain \n \n Empowering Analysts \n \n NL2KQL shifts the focus from learning and troubleshooting query syntax to investigating and mitigating threats. By reducing the cognitive load, analysts can spend more time on high-value tasks, such as identifying attack patterns and responding to incidents. \n \n Improving Efficiency \n \n In scenarios where speed is essential, NL2KQL accelerates query creation, enabling analysts to retrieve insights faster. Whether investigating malware propagation or monitoring insider threats, NL2KQL reduces time-to-insight. \n \n Democratizing Security Analysis \n \n With NL2KQL, less experienced analysts can contribute meaningfully to investigations without needing extensive training in KQL. This democratization is particularly valuable as the demand for skilled cybersecurity professionals continues to outpace supply. \n \n Future-Ready Security \n \n The security landscape is constantly evolving, with new threats and data sources emerging daily. NL2KQL’s adaptability ensures it can scale to support diverse use cases and data schemas, making it a future-ready tool for SOCs. \n   \n Where to Learn More \n \n Data: Repo Link \n Paper: arXiv:2404.02933 \n \n If you use the NL2KQL code, data, results, or any related resources in your research, please cite: \n @article{tang2025nl2kqlnaturallanguagekusto, \n   title={NL2KQL: From Natural Language to Kusto Query}, \n   author={Xinye Tang and Amir H. Abdi and Jeremias Eichelbaum and Mahan Das and Alex Klein and Nihal Irmak Pakis and William Blum and Daniel L Mace and Tanvi Raja and Namrata Padmanabhan and Ye Xing}, \n   journal={arXiv preprint arXiv:2404.02933}, \n   year={2025} \n } ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"7600","kudosSumWeight":3,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzg4OTMwLWxQeG5qVQ?revision=9\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzg4OTMwLWszUEJMMA?revision=9\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDM","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzg4OTMwLXppS0ZzWg?revision=9\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDQ","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzg4OTMwLTdMVmtuWg?revision=9\"}"}}],"totalCount":4,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":{"__typename":"UploadedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzg4OTMwLWxQeG5qVQ?revision=9"},"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:4384386":{"__typename":"Conversation","id":"conversation:4384386","topic":{"__typename":"BlogTopicMessage","uid":4384386},"lastPostingActivityTime":"2025-02-28T09:00:00.022-08:00","solved":false},"User:user:2237870":{"__typename":"User","uid":2237870,"login":"vbeizer","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/dS0yMjM3ODcwLVNmM0hwRQ?image-coordinates=0%2C163%2C1543%2C1706"},"id":"user:2237870"},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzg0Mzg2LTR0UXBoUQ?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzg0Mzg2LTR0UXBoUQ?revision=5","title":"Security-Texture-TechScan-Green-03.jpg","associationType":"COVER","width":4096,"height":2304,"altText":""},"BlogTopicMessage:message:4384386":{"__typename":"BlogTopicMessage","subject":"Azure Lighthouse support for MSSP use of Security Copilot Sentinel scenarios in Public Preview","conversation":{"__ref":"Conversation:conversation:4384386"},"id":"message:4384386","revisionNum":5,"uid":4384386,"depth":0,"board":{"__ref":"Blog:board:SecurityCopilotBlog"},"author":{"__ref":"User:user:2237870"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":2629},"postTime":"2025-02-28T09:00:00.022-08:00","lastPublishTime":"2025-02-28T09:00:00.022-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Security Copilot support for Azure Lighthouse Sentinel use cases for managed security service provider (MSSP) tenants is now in public preview. With this support, MSSPs can purchase SCUs and attach them to the managing tenant in Azure Lighthouse and use those SCUs to run Security Copilot skills related to Microsoft Sentinel on their customer tenants via Azure Lighthouse. All the Sentinel skills available in Security Copilot will be invokable from the Azure Lighthouse tenant without the customer needing to have Security Copilot, thereby making Security Copilot available to MSSPs who manage multiple customers. \n Supported scenarios include querying the customer Sentinel incident, incident entities/ details, querying Sentinel workspaces, and fetching Sentinel incident query. These skills can be invoked on per customer Sentinel workspace. Managing tenants using Azure Lighthouse now can do the following, without their customers needing to provision SCUs: \n \n Use the same natural language based prompts using Sentinel skills on customer data \n Create custom promptbooks using Sentinel skills to automate their investigations \n Use Logic Apps to trigger these promptbooks \n \n While this release doesn’t support all Security Copilot skills across customer tenants for MSSPs, it is an important development on the road to full support for Security Copilot for MSSPs using Azure Lighthouse. Read on to learn more about what this means for your practice, and how to get started. \n What is Azure Lighthouse?  \n Azure Lighthouse is built into the Azure portal and allows IT partners to manage multiple tenants for Azure services. It provides a unified management experience, enabling partners to view and manage resources across all their customers' Azure environments from a single pane of glass. It supports multi-customer management, meaning partners can perform actions across multiple customer tenants simultaneously. This is particularly useful for Managed Service Providers (MSPs) who need to manage resources at scale.  \n What is changing?   \n We are introducing Azure Lighthouse support for MSSPs to use Security Copilot on their customer tenants without requiring customers to purchase Security Compute Units (SCUs). With Azure Lighthouse support, SCUs should be purchased by a MSSP admin  for use on their customer’s tenant . To get started, MSSPs can go to Azure to onboard on to Security Copilot and apply their purchased SCUs to their Azure Lighthouse subscription. In Azure Lighthouse, the MSSP needs to ensure that they have access setup to their customer’s Sentinel environment. \n Once the setup is completed, MSSPs can invoke Sentinel skills on the customer tenant via the Security Copilot Standalone portal and use the SCUs associated to the Azure Lighthouse subscription. MSSPs can further use custom promptbooks and logic apps to automate their workflows. \n In future, managed service support will continue to expand to include other skills and capabilities such as Entra, Intune and Purview skills. We will also add support to run the skills in parallel on multiple workspaces across customer tenants so that the same prompt can return the response from multiple tenants for better analysis.   \n What other access controls are supported?   \n As of December 2024, we now support M365 Partner Center GDAP (Granular Delegated Admin Privileges) which allows the managing tenant to operate directly in their customer’s environment using their customer’s Security Copilot tenant. \n M365 Partner Center GDAP:  \n GDAP is focused on Microsoft 365 services and is available through the Partner Center. It provides more granular and time-bound access to customer workloads, addressing security concerns by offering least-privileged access. Unlike Azure Lighthouse, GDAP relationships are more specific and time-bound, with a maximum duration of two years. Partners can request and manage these relationships through the Partner Center. GDAP is designed to help partners provide services to customers who have regulatory requirements or security concerns about high levels of partner access. \n MSSPs can get access to customer tenants via GDAP and log into the Security Copilot standalone portal or the embedded experience to get their jobs done. The MSSP will be able to execute all the skills in Security Copilot (Entra, Defender, Purview, Intune, XDR etc.,), a full list of skills is available here  as GDAP supports all these services. In this configuration, the customer is the one purchasing Security Copilot SCUs and the MSSP uses these SCUs associated to the customer tenant, rather than SCUs associated to the MSSP’s tenant. \n Since Entra, Defender, Purview, Intune are not supported in Azure Lighthouse, the only way for MSSPs to use Security Copilot on their customer tenant for these products is by directly logging into the customer tenant and utilizing the SCUs purchased by customers. \n   \n Additional Resources \n Understand authentication in Microsoft Security Copilot | Microsoft Learn \n Grant MSSPs access to Microsoft Security Copilot | Microsoft Learn \n Microsoft Security Copilot Frequently Asked Questions | Microsoft Learn \n Microsoft 365 Lighthouse frequently asked questions (FAQs)  \n GDAP frequently asked questions - Partner Center | Microsoft Learn  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Fluent Bit with Microsoft Sentinel","conversation":{"__ref":"Conversation:conversation:4377725"},"id":"message:4377725","revisionNum":9,"uid":4377725,"depth":0,"board":{"__ref":"Blog:board:MicrosoftSentinelBlog"},"author":{"__ref":"User:user:452290"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"If you’re using Fluent bit within your organization already for log processing, then integrating with Microsoft Sentinel is also a possibility as Fluent Bit has the output plugin for Azure Logs Ingestion API taking leverage from the Log Ingestion API which supports not only ingestion for custom tables but also for built-in tables.","metrics":{"__typename":"MessageMetrics","views":959},"postTime":"2025-02-14T10:06:16.117-08:00","lastPublishTime":"2025-02-14T10:06:16.117-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" This guide will walk you through the steps required to integrate Fluent Bit with Microsoft Sentinel. Beware that in this article, we assume you already have a Sentinel workspace, a Data Collection Endpoint and a Data Collection Rule, an Entra ID application and finally a Fluent Bit installation.  \n As mentioned above, log ingestion API supports ingestion both in custom tables as built-in tables, like CommonSecurityLog, Syslog, WindowsEvent and more.  In case you need to check which tables are supported please the following article: https://learn.microsoft.com/en-us/azure/azure-monitor/logs/logs-ingestion-api-overview#supported-tables \n Prerequisites:  \n Before beginning the integration process, ensure you have the following: \n \n \n An active Azure subscription with Microsoft Sentinel enabled; \n \n \n Microsoft Entra ID Application taking note of the ClientID, TenantID and Client Secret – create one check this article: https://learn.microsoft.com/en-us/entra/identity-platform/quickstart-register-app?tabs=certificate \n \n \n A Data Collection Endpoint (DCE) – to create a data collection endpoint, please check this article: https://learn.microsoft.com/en-us/azure/azure-monitor/essentials/data-collection-endpoint-overview?tabs=portal \n \n \n A Data Collection Rule (DCR) – fields from the Data Collection Rule need to match exactly to what exists in table columns and also the fields from the log source. To create a DCR please check this article: https://learn.microsoft.com/en-us/azure/azure-monitor/essentials/data-collection-rule-create-edit?tabs=cli \n \n \n Depending on the source, it might require a custom table to be created or an existing table from log analytics workspace; \n \n \n Fluent Bit installed on your server or container – In case you haven’t yet installed Fluent Bit, in the following article you'll find the instructions per type of operating system: https://docs.fluentbit.io/manual/installation/getting-started-with-fluent-bit \n \n \n High level architecture: \n   \n \n Step 1: Setting up Fluent Big configuration file \n Before we step-in into the configuration, Fluent Bit has innumerous output plugins and one of those is through Log Analytics Ingestion API both to supported Sentinel tables but also for custom tables. \n You can check more information about it here in Fluent Bit documentation: https://docs.fluentbit.io/manual/pipeline/outputs/azure_logs_ingestion \n Moving forwarder, in order to configure Fluent Bit to send logs into Sentinel log analytics workspace, please take note of the specific input plugin you are using or intend to use to receive logs and how can you use it to output the logs to Sentinel workspace. \n For example most of the Fluent Bit plugins allow to set a “tag” key which can be used within the output plugin so that there’s a match in which logs are intended to send. On the other hand, in a scenario where multiple input plugins are used and all are required send logs to Sentinel, then a match of type wildcard \"*\" could be used as well.   \n Another example, in a scenario where there are multiple input plugins of type “HTTP” and you want to just send a specific one into Sentinel, then the “match” field must be set according to the position of the required input plugin, for example “match http.2”, if the input plugin would the 3 rd in the list of HTTP inputs. If nothing is specified in the \"match\" field, then it will assume \"http.0\" by default.  \n For better understanding, here’s an example of how a Fluent Bit config file could look:  \n First, the configuration file is located under the path ”/etc/fluent-bit/fluent-bit.conf” \n The first part is the definition of all “input plugins”, then follows the “filter plugins” which you can use for example to rename fields from the source to match for what exists within the data collection rule schema and Sentinel table columns and finally there’s the output plugins. \n Below is a screenshot of a sample config file: \n INPUT plugins section: In this example we’re going to use the “dummy input” to send sample messages to Sentinel. However, in your scenario you could leverage other’s input plugins within the same config file. \n \n After everything is configured in the input section, make sure to complete the “FILTER” section if needed, and then move forward to the output plugin section, screenshot below. \n OUTPUT plugins section: In this section, we have output plugins to write on a local file based on two tags “dummy.log” and “logger”, an output plugin that prints the outputs in json format and the output plugin responsible for sending data to Microsoft Sentinel. \n As you can see, this one is matching the “tag” for “dummy.log” where we’ve setup the message “{“Message”:”this is a sample message for testing fluent bit integration to Sentinel”, “Activity”:”fluent bit dummy input plugn”, “DeviceVendor”:”Ubuntu”}.   \n Make sure you insert the correct parameters in the output plugin, in this scenario the \"azure_logs_ingestion\" plugin.  \n \n Step 2: Fire Up Fluent Bit \n When the file is ready to be tested please execute the following: \n \n \n sudo /opt/fluent-bit/bin/fluent-bit -c /etc/fluent-bit/fluent-bit.conf \n \n \n Fluent bit will start initialization all the plugins it has under the config file. \n \n Then you’re access token should be retrieved if everything is well setup under the output plugin (app registration details, data collection endpoint URL, data collection rule id, sentinel table and important to make sure the name of the output plugin is actually “azure_logs_ingestion”). \n \n In a couple of minutes you should see this data under your Microsoft Sentinel table, either an existing table or a custom table created for the specific log source purpose. \n \n Summary \n Integrating Fluent Bit with Microsoft Sentinel provides a powerful solution for log collection and analysis. By following this guide, hope you can set up a seamless integration that enhances your organization's ability to monitor and respond to security threats, just carefully ensure that all fields processed in Fluent Bit are mapped exactly to the fields in Data Collection Rule and Sentinel table within Log Analytics Workspace. \n Special thanks to “Bindiya Priyadarshini” that collaborated with me on this blog post. \n Cheers! 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tle":"image.png","associationType":"BODY","width":975,"height":489,"altText":""},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzc5MDE5LTFIeHUyYQ?revision=2\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzc5MDE5LTFIeHUyYQ?revision=2","title":"image.png","associationType":"BODY","width":975,"height":489,"altText":""},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzc5MDE5LUZMWE9iQg?revision=2\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzc5MDE5LUZMWE9iQg?revision=2","title":"image.png","associationType":"BODY","width":974,"height":487,"altText":""},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzc5MDE5LTBTQlU3SA?revision=2\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzc5MDE5LTBTQlU3SA?revision=2","title":"image.png","associationType":"BODY","width":975,"height":490,"altText":""},"BlogTopicMessage:message:4379019":{"__typename":"BlogTopicMessage","subject":"Introducing Threat Intelligence Ingestion Rules","conversation":{"__ref":"Conversation:conversation:4379019"},"id":"message:4379019","revisionNum":2,"uid":4379019,"depth":0,"board":{"__ref":"Blog:board:MicrosoftSentinelBlog"},"author":{"__ref":"User:user:773864"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"Boost Your Threat Intel Game with Microsoft Sentinel’s New Curation at Scale","metrics":{"__typename":"MessageMetrics","views":3540},"postTime":"2025-02-14T08:39:36.410-08:00","lastPublishTime":"2025-02-14T08:39:36.410-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Microsoft Sentinel just rolled out a powerful new public preview feature: Ingestion Rules. This feature lets you fine-tune your threat intelligence (TI) feeds before they are ingested to Microsoft Sentinel. You can now set custom conditions and actions on Indicators of Compromise (IoCs), Threat Actors, Attack Patterns, Identities, and their Relationships. \n Use cases include: \n \n Filter Out False Positives: Suppress IoCs from feeds known to generate frequent false positives, ensuring only relevant intel reaches your analysts. \n Extending IoC validity periods for feeds that need longer lifespans. \n Tagging TI objects to match your organization's terminology and workflows \n \n Get Started Today with Ingestion Rules \n To create new “Ingestion rule”, navigate to “Intel Management” and Click on “Ingestion rules” \n With the new Ingestion rules feature, you have the power to modify or remove indicators even before they are integrated into Sentinel. These rules allow you to act on indicators currently in the ingestion pipeline. \n > Click on “Ingestion rules”\n Note: It can take up to 15 minutes for the rule to take effect \n Use Case #1: Delete IOC’s with less confidence score while ingesting \n When ingesting IOC's from TAXII/Upload API/File Upload, indicators are imported continuously. With pre-ingestion rules, you can filter out indicators that do not meet a certain confidence threshold. Specifically, you can set a rule to drop all indicators in the pipeline with a confidence score of 0, ensuring that only reliable data makes it through. \n \n Use Case #2: Extending IOC’s \n The following rule can be created to automatically extend the expiration date for all indicators in the pipeline where the confidence score is greater than 75. This ensures that these high-value indicators remain active and usable for a longer duration, enhancing the overall effectiveness of threat detection and response. \n \n Use Case #3: Bulk Tagging \n Bulk tagging is an efficient way to manage and categorize large volumes of indicators based on their confidence scores. With pre-ingestion rules, you can set up a rule to tag all indicators in the pipeline where the confidence score is greater than 75. This automated tagging process helps in organizing indicators, making it easier to search, filter, and analyze them based on their tags. It streamlines the workflow and improves the overall management of indicators within Sentinel. \n \n Managing Ingestion rules \n In addition to the specific use cases mentioned, managing ingestion rules gives you control over the entire ingestion process. \n 1. Reorder Rules \n You can reorder rules to prioritize certain actions over others, ensuring that the most critical rules are applied first. This flexibility allows for a tailored approach to data ingestion, optimizing the system's performance and accuracy.  \n \n 2. Create From \n Creating new ingestion rules from existing ones can save you a significant amount of time and offer the flexibility to incorporate additional logic or remove unnecessary elements. Effectively duplicating these rules ensures you can quickly adapt to new requirements, streamline operations, and maintain a high level of efficiency in managing your data ingestion process. \n \n 3. Delete Ingestion Rules \n Over time, certain rules may become obsolete or redundant as your organizational needs and security strategies evolve. It's important to note that each workspace is limited to a maximum of 25 ingestion rules. Having a clean and relevant set of rules ensures that your data ingestion process remains streamlined and efficient, minimizing unnecessary processing and potential conflicts. \n Deleting outdated or unnecessary rules allows for a more focused approach to threat detection and response. It reduces clutter, which can significantly enhance the performance. By regularly reviewing and purging obsolete rules, you maintain a high level of operational efficiency and ensure that only the most critical and up-to-date rules are in place. \n \n Conclusion \n By leveraging these pre-ingestion rules effectively, you can enhance the quality and reliability of the IOC’s ingested into Sentinel, leading to more accurate threat detection and an improved security posture for your organization. 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A real-world incident investigation will showcase the features and impact these plugins bring to the table.","metrics":{"__typename":"MessageMetrics","views":1854},"postTime":"2025-02-07T08:00:00.017-08:00","lastPublishTime":"2025-02-07T08:00:00.017-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":"   \n   \n   \n   \n   \n The Security Copilot custom plugin empowers you to extend Security Copilot functionalities beyond the preinstalled and third-party plugins. This blog introduces two custom plugins that you can install and use in your environment. An incident investigation case study will be used to demonstrate the features of these two custom plugins. Additionally, a step-by-step guide will walk you through the setup process, which only takes a few clicks. \n The first custom plugin, “Custom Plugin Defender Device Investigation”, provides the following skills: \n Title: File - Files Downloaded \n \n Description: Lists files downloaded to this device in specific timeframe within past 30 days. \n \n Title: File - Last 15 Days Files Downloaded \n \n Description: Lists files downloaded to this device in the last 15 days. \n \n Title: File - Any Device Events Related To This File \n \n Description: Display device events that include the filename, in specific timeframe. \n \n Title: File - Sensitive Files Events \n \n Description: Lists sensitive files events on this device in the last 10 days. \n \n Title: File - File Origin \n \n Description: Display the origin or source of the file, in past 30 days. \n \n Title: Process - Process Executions Summary \n \n Description: Summary of process executions on this device in specific timeframe. \n \n Title: Process - Detailed Process Executions \n \n Description: Detailed all process execution events on device within a brief period, e.g. an hour. \n \n Title: Process - Detailed Process Events \n \n Description: Detailed specific process execution events on device within a defined time frame. \n \n Title: Lateral Movement - RDP To Device \n \n Description: Inbound RDP connection to this device in a specific timeframe. \n \n Title: Lateral Movement - Logon To Device \n \n Description: Logon events from other devices to this device in a specific timeframe. \n \n Title: Lateral Movement - Logons To Device In Last 10 Days \n \n Description: Logon events from other devices to this device in the last 10 days. \n \n Title: Network - Outbound Network Events \n \n Description: Device outbound network events, including attempts and failed connections. \n \n Title: Network - Inbound Network Events \n \n Description: Device inbound network events and attempts in a specific timeframe. \n \n Title: Network - Device Listening Ports \n \n Description: Displays device listening ports in specific timeframe. \n \n Title: Device Events - Scheduled Task Events \n \n Description: Scheduled task events seen on a device in a specific timeframe. \n \n Title: Device Events - User Account Events \n \n Description: User account events seen on a device in a specific timeframe. \n \n Title: Device Events - User Account Added Or Removed From Local Group \n \n Description: User account added or removed from local group in a specific timeframe. \n \n Title: Suspicious Activities - ASR Rules Triggered \n \n Description: ASR rules that were triggered on this device in the past 7 days. \n \n Title: Suspicious Activities - ASMSI Script Detection \n \n Description: Script detection from Windows Antimalware Scan Interface (AMSI) in past 7 days. \n \n Title: Suspicious Activities - Exploit Guard Events \n \n Description: Exploit Guard events detected on this device in past 7 days. \n \n Title: Suspicious Activities - Network Protection Events \n \n Description: Network Protection events triggered on this device in the past 7 days. \n \n Title: Suspicious Activities - Device Tampering Attempts \n \n Description: Possible tampering attempts on this device in the past 7 days. \n \n   \n The second custom plugin, “Custom Plugin Defender Device Info”, offers specific device information often needed during an investigation. Its skills include: \n Title: Device OS Information \n \n Description: Latest device OS information with the device name as the input. \n \n Title: Device Current and Past IPs \n \n Description: The current and past IPs assigned to this device in the last 10 days. \n \n Title: Device Users and Login Counts \n \n Description: List users logged onto this device and the number of times, within the last 10 days. \n \n Title: Device Alert Information \n \n Description: Alerts observed on this device in the last 30 days. \n \n Title: Device Installed Applications \n \n Description: Currently installed applications on this device. \n \n Title: Device Vulnerability Information \n \n Description: Vulnerabilities identified on this device. \n \n Title: Device Critical Vulnerabilities \n \n Description: Vulnerability with CVSS score 7 or higher, or exploit is publicly available. \n \n   \n Both custom plugins are available for download from the Security Copilot GitHub repository at this link. Step-by-step guides on how to install the custom plugin will be covered later in this blog. \n Let's start by demonstrating some of the capabilities of the two custom plugins through a case study of a Microsoft Defender XDR incident. \n   \n \n For this incident, the Security Copilot incident summary reveals that the threat actor used a credential phishing attack to gain initial access. Over the course of the incident, several instances of lateral movement, credential access, and privilege escalation were detected, impacting users and devices across the network. Key activities included the use of tools like Mimikatz and Rubeus, suspicious remote sessions, and evidence of system manipulation. \n From the Security Copilot incident summary, you learn that the attack started when user “jonaw” clicked on a malicious URL in an email. Following that, a suspicious remote session was detected on device “vnevado-win10v”. To investigate the suspicious remote session on the device, one way is to leverage the “Lateral Movement – Logon To Device” skill from the “Custom Plugin Defender Device Investigation” plugin in Security Copilot's standalone mode. This skill presents the logon events that occurred on the device within the specified timeframe. The logon events include console logons, Remote Desktop logons, remote registry logons, scheduled task logons, and more. \n You can invoke this skill by navigating to the System Capabilities menu option from the prompt bar. To get to the System Capabilities menu option, select the Prompts option from the prompt bar, as shown next. \n \n Then the System Capabilities menu option appears. \n \n This skill is located under the plugin named “CUSTOM PLUGIN DEFENDER DEVICE INVESTIGATION”, as shown next. \n \n Once this skill is selected, you will need to fill in three input fields: the device name, start time, and end time. For this case study, the alert for the suspicious remote session was triggered for device vnevado-win10v, occurring at approximately 9:42 UTC on November 22 nd 2024. For the investigation, let's set the start time to 2024-11-22 9:30 UTC and the end time to 9:50 UTC, as shown in the next screenshot. \n \n The next screenshot demonstrates that Security Copilot executes this skill. \n \n Using the “Export to Excel” option in the Copilot response, you can download then manually review the logon events. Upon inspection, it is discovered that for device vnevado-win10v, there is a long list of logon events involving different user accounts within the 20-minute time frame. A screenshot showing a portion of the logon events is displayed next. \n \n   \n You can then ask Security Copilot with this prompt: “Can you review the previous output of the logon events for the device vnevado-win10v between 2024-11-22 09:30 and 2024-11-22 09:50, summarize the logon events and also point out anything suspicious”. The next screenshot displays the Security Copilot prompt along with the beginning of its response. \n \n The logon event summary provided by Security Copilot is thorough but a bit long. At the end, it includes the identified suspicious logon activities: \n \n There are several instances where logon attempts are followed by successful logons within milliseconds, which could indicate automated or scripted logon attempts. \n There are 10 logon events with an \"Unknown\" logon type, which is unusual and may warrant further investigation. \n The account debrab has one logon event where it is marked as a local admin, which should be verified for legitimacy. \n \n For your reference, the last section of the Security Copilot’s logon event summary is shown in the next screen capture. \n \n After reviewing the logon event summary for device vnevado-win10v, let’s find out who might be the owner of this device. The “Device Users and Login Counts” skill from the “Custom Plugin Defender Device Info” plugin provides a summary of how many times each user has logged into the device over the past 30 days. Typically, the user with the most logins is likely the device owner. \n Once the skill is executed for device vnevado-win10v, Security Copilot reports that “user jonaw has logged onto the device vnevado-win10v a total of 189 times in the last 30 days”, as shown in the next screen capture. This helps to identify user “jonaw” as the likely device owner, which in turn makes user “debrab” appear even more suspicious. \n \n   \n Let’s go back to the detailed logon events provided by Security Copilot earlier and take another look at user account “debrab”. The next screenshot shows the logon events for device vnevado-win10v, filtered to display only those associated with the user “debrab”. One notable observation is that the logon type for user “debrab” is either batch or unknown, which appears suspicious as well, especially with one batch logon with local admin privilege. \n \n What is a batch logon type? You can ask Security Copilot for more insights. The next screenshot displays Copilot’s responses, which explains that a batch logon type is typically used for scheduled tasks. \n \n The batch logon seems odd in this case. One of Security Copilot's key features is its ability to distinguish between normal and anomalous behavior in IT operations. In this case, let’s ask Security Copilot whether it’s common for someone with local admin privilege to log on to a device through a batch logon. \n \n As seen in the previous screenshot, Security Copilot points out that the batch logon is unusual, as it is typically used for scheduled tasks or automated processes, not for interactive sessions by administrators. Security Copilot’s response further confirms that the batch logon events with user account “debrab” are suspicious. This information and the other Security Copilot observations can assist you in identifying the suspicious remote session detected on device “vnevado-win10v”. \n   \n The incident summary generated by Security Copilot not only mentions the detection of a suspicious remote session on device vnevado-win10v, but also reports the presence of suspicious files, including mimikatz.exe, rubeus.exe, xcopy.exe, and powershell.exe. The incident summary snippet is displayed next for reference. \n \n Let’s now examine what occurred on the device involving these suspicious files. A quick and easy way to start the investigation is to check for files downloaded to the device and reviewing the device's process execution events around the time of the incident to identify anything suspicious. \n Manually checking for downloaded files and examining process execution events can be time-consuming and labor-intensive. However, with the help of Security Copilot, these tasks can be performed more quickly and efficiently. \n The “File - Files Downloaded” skill from the “Custom Plugin Defender Device Investigation” plugin can be used to quickly identify files that were downloaded onto a device within a specific time period. Then, the “Process - Process Executions Summary” skill from the same Security Copilot plugin can be used to list the processes that executed on the device during the same timeframe. You can then ask Security Copilot to analyze these processes to identify anything suspicious. \n After the “File - Files Downloaded” skill executes, Security Copilot identifies a file named DomainDominance198.zip was downloaded to device vnevado-win10v. \n \n Another thing to keep in mind is that not all the information from the Copilot findings is directly visible in the Security Copilot console. You can expand the output result within the console or export the findings to Excel for a clearer view of the additional details. For this investigation, you can then more thoroughly review the URL from which the file was downloaded, verify the file location through its folder path, and locate the user account associated with the download. The next screenshot displays these additional details seen in the Excel spreadsheet. \n \n Then, the “Process - Process Executions Summary” skill provides a list of processes executed on the same device, vnevado-win10v, during the same period. \n \n Instead of manually reviewing all 128 processes, you can ask Security Copilot to analyze the processes and flag any suspicious ones. In addition, it's worth mentioning earlier in the investigation, leveraging the Microsoft Entra plugin, Security Copilot reports that user account “jonaw” belongs to Jonathan Wolcott, an account executive in the Sales department. \n \n With this information, let’s ask Security Copilot to identify any process execution that should typically not be carried out by someone outside of the IT department. Here is the Security Copilot prompt you can use: User “jonaw” is an account executive in the sales department, with this information, can you identify any processes that typically should not be carried out by someone outside of the IT department? \n Security Copilot then identifies six suspicious processes and provides its reasoning along the way. \n \n Once again, you can export the Security Copilot findings to Excel for a more thorough review. The next screenshot displays the results in Excel, with a more readable format. \n \n   \n Now that a few more suspicious processes have been identified, let's revisit the downloaded file, DomainDominance198.zip, to see if more details can be uncovered. \n The skill, “File - Any Device Events Related To This File”, is part of the “Custom Plugin Defender Device Investigation” plugin in Security Copilot. It is designed to identify any device events or activities related to a specific file. It uses the filename as a keyword to filter and display only the device events containing this keyword within a defined time period. For this security incident, let's use this skill to search for device events containing the name of the downloaded file, DomainDominance198. \n \n Upon reviewing the Security Copilot response exported to Excel, you can see that a new file, DomainDominance198.ps1, has been created in the same directory as DomainDominance198.zip. \n \n   \n In addition, the “File - File Origin” skill in the “Custom Plugin Defender Device Investigation” plugin provides details about a file's origin or source. It shows where the file came from, and any associated file or connection linked to it. In this case, as shown in the next screenshot, Security Copilot reveals that the file DomainDominance198.zip was downloaded from a specific URL. \n \n And that the file DomainDominance198.ps1 is associated with file DomainDominance198.zip, as shown next. \n \n The additional details in Security Copilot’s responses highlight the exact association, indicating that the File Origin Referrer URL for DomainDominance198.ps1 is DomainDominance198.zip, as shown in the next screen capture. \n \n   \n With these insights, let's use another Security Copilot skill to conduct a more in-depth examination of PowerShell execution events on device vnevado-win10v. The skill, “Process - Detailed Process Events”, is also part of the “Custom Plugin Defender Device Investigation” plugin. It retrieves detailed process execution events, including process command line information and the parent process execution details, for the specified process on a given device within a defined time frame. \n When this skill is invoked, it requires four mandatory fields to be filled, as shown next. \n \n Security Copilot then displays the PowerShell execution events identified on device vnevado-win10v within the specified timeframe of 2024-11-22 09:30 to 2024-11-22 10:30, as shown next. \n \n From a more condensed text view of the responses from Security Copilot, a range of unusual or potentially harmful behaviors can be observed in the next screenshot. Some of these suspicious events are highlighted in yellow or displayed in bold in the next screenshot. \n \n The process execution events retrieved include command line details and parent process, therefore you are able to see both the PowerShell execution and processes launched with PowerShell as the parent process. The suspicious processes, such as mimikatz.exe, Rubeus.exe, xcopy.exe, PxExec.exe, and others mentioned in the Security Copilot incident summary, are identified here, allowing you to quickly recognize the correlation. \n Additionally, you can ask Security Copilot to assist you in reviewing the suspicious events. For instance, immediately after the xcopy command was used to copy the file “Rubeus.exe” to the remote device vnevado-win10b, a subsequent command involving “PsExec.exe” is observed in the detailed PowerShell execution events presented earlier by Security Copilot. The two command lines are shown in the next screen capture. \n \n Consulting with Security Copilot reveals that “PsExec.exe” executed a command remotely on the device vnevado-win10b. This command launched “Rubeus.exe” to dump Kerberos tickets for the user “nestorw” and saved the output to C:\\Temp\\AdminTicket.txt. Security Copilot notes that this action indicates credential dumping and potential lateral movement within the network. The next screenshot shows the prompt along with part of the responses from Security Copilot. \n \n As there are many other potentially harmful behaviors also observed in the detailed PowerShell execution events presented by Security Copilot earlier, you can submit each of these suspicious events to Security Copilot and ask for insights. \n Downloading and Installing the Custom Plugins \n The configuration files for the custom plugins can be downloaded from this link. Once you have the configuration file (in YAML format), here are the steps to upload and install it to your Security Copilot instance. \n Step 1: Select the Sources icon in the Prompt bar. \n \n Step 2: Scroll to the bottom of the Manage Sources page, within the Custom section, you'll find the \"Add a plugin\" option. \n \n Step 3: Click on “Add plugin” and then choose “Copilot for Security plugin”, as illustrated in the next screenshot.  \n \n Step 4: Click on “Upload file” to install configuration file, which is in YAML format. \n \n Step 5: Click on Add. And voilà, the new custom plugin appears along with other plugins in the Manage sources section, as seen in the screen capture next. \n \n Now you can start using the custom plugins and they will appear in the “System Capabilities” section. 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