Announcing Public Preview: New STIX Objects in Microsoft Sentinel
Security teams often struggle to understand the full context of an attack. In many cases, they rely solely on Indicators of Compromise (IoCs) without the broader insights provided by threat intelligence developed on Threat Actors, Attack Patterns, Identities - and the Relationships between each. This lack of context available to enrich their workflows limits their ability to connect the dots, prioritize threats effectively, and respond comprehensively to evolving attacks. To help customers build out a thorough, real-time understanding of threats, we are excited to announce the public preview of new Threat Intelligence (TI) object support in Microsoft Sentinel and in the Unified SOC Platform. In addition to Indicators of Compromise (IoCs), Microsoft Sentinel now supports Threat Actors, Attack Patterns, Identities, and Relationships. This enhancement empowers organizations to take their threat intelligence management to the next level. In this blog, we’ll highlight key scenarios for which your team would use STIX objects, as well as demos showing how to create objects and new relationships and how to use them to hunt threats across your organization Key Scenarios STIX objects are a critical tool for incident responders attempting to understand an attack and threat intelligence analysts seeking more information on critical threats. It is designed to improve interoperability and sharing of threat intelligence across different systems and organizations. Below, we’ve highlighted four ways Unified SOC Platform customers can begin using STIX objects to protect their organization. Ingesting Objects: You can now ingest these objects from various commercial feeds through several methods including STIX TAXII servers, API, files, or manual input. Curating Threat Intelligence: Curate and manage any of the supported Threat Intelligence objects. Creating Relationships: Establish connections between objects to enhance threat detection and response. For example: Connecting Threat Actor to Attack Pattern: The threat actor "APT29" uses the attack pattern "Phishing via Email" to gain initial access. Linking Indicator to Threat Actor: An indicator (malicious domain) is attributed to the threat actor "APT29". Associating Identity (Victim) with Attack Pattern: The organization "Example Corp" is targeted by the attack pattern "Phishing via Email". Hunt and Investigate Threats More Effectively: Match curated TI data against your logs in the unified SOC platform powered by Microsoft Sentinel. Use these insights to detect, investigate, and hunt threats more efficiently, keeping your organization secure. Get Started Today with the new Hunting Model The ability to ingest and manage these new Threat Intelligence objects is now available in public preview. To enable this data in your workspaces for hunting and detection, submit your request here and we will provide further details. Demo and screen shots Demo 1: Hunt and detect threats using STIX objects Scenario: Linking an IOC to a Threat Actor: An indicator (malicious domain) is attributed to the threat actor " Sangria tempest " via the new TI relationship builder. Please note that the Sangria tempest actor object and the IOC are already present in this demo. These objects can be added automatically or created manually. To create new relationship, sign into your Sentinel instance and go to Add new à TI relationship. In the New TI relationship builder, you can select existing TI objects and define how it's related to one or more other TI objects. After defining a TI object’s relationship, click on “Common” to provide metadata for this relationship, such as Description, Tags, and Confidence score: p time, source, and description. Another type of meta data a customer can add to a relationship is the Traffic Light Protocol (TLP). The TLP is a set of designations used to ensure that sensitive information is shared with the appropriate audience. It uses four colors to indicate different levels of sensitivity and the corresponding sharing permissions: TLP:RED: Information is highly sensitive and should not be shared outside of the specific group or meeting where it was originally disclosed. TLP:AMBER: Information can be shared with members of the organization, but not publicly. It is intended to be used within the organization to protect sensitive information. TLP:GREEN: Information can be shared with peers and partner organizations within the community, but not publicly. It is intended for a wider audience within the community. TLP:WHITE: Information can be shared freely and publicly without any restrictions. Once the relationship is created, your newly created relationship can be viewed from the “Relationships” tab. Now, retrieve information about relationships and indicators associated with the threat actor 'Sangria Tempest'. For Microsoft Sentinel customers leveraging the Azure portal experience, you can access this in Log Analytics. For customers who have migrated to the unified SecOps platform in the Defender portal, you can go find this under “Advanced Hunting”. The following KQL query provides you with all TI objects related to “Sangria Tempest.” You can use this query for any threat actor name. let THREAT_ACTOR_NAME = 'Sangria Tempest'; let ThreatIntelObjectsPlus = (ThreatIntelObjects | union (ThreatIntelIndicators | extend StixType = 'indicator') | extend tlId = tostring(Data.id) | extend StixTypes = StixType | extend Pattern = case(StixType == "indicator", Data.pattern, StixType == "attack-pattern", Data.name, "Unkown") | extend feedSource = base64_decode_tostring(tostring(split(Id, '---')[0])) | summarize arg_max(TimeGenerated, *) by Id | where IsDeleted == false); let ThreatActorsWithThatName = (ThreatIntelObjects | where StixType == 'threat-actor' | where Data.name == THREAT_ACTOR_NAME | extend tlId = tostring(Data.id) | extend ActorName = tostring(Data.name) | summarize arg_max(TimeGenerated, *) by Id | where IsDeleted == false); let AllRelationships = (ThreatIntelObjects | where StixType == 'relationship' | extend tlSourceRef = tostring(Data.source_ref) | extend tlTargetRef = tostring(Data.target_ref) | extend tlId = tostring(Data.id) | summarize arg_max(TimeGenerated, *) by Id | where IsDeleted == false); let SourceRelationships = (ThreatActorsWithThatName | join AllRelationships on $left.tlId == $right.tlSourceRef | join ThreatIntelObjectsPlus on $left.tlTargetRef == $right.tlId); let TargetRelationships = (ThreatActorsWithThatName | join AllRelationships on $left.tlId == $right.tlTargetRef | join ThreatIntelObjectsPlus on $left.tlSourceRef == $right.tlId); SourceRelationships | union TargetRelationships | project ActorName, StixTypes, ObservableValue, Pattern, Tags, feedSource You now have all the information your organization has available about Sangria Tempest, correlated to maximize your understanding of the threat actor and its associations to threat infrastructure and activity. Demo 2: Curate and attribute objects We have created new UX to streamline TI object creation, which includes the capability to attribute to other objects, so while you are creating a new IoC, you can also attribute that indicator to a Threat Actor, all from one place. To create a new TI object and attribute it to one or multiple threat actors, follow the steps below: Go to Add new a TI Object. In the Context menu, select any object type. Enter all the required information in the fields on the right-hand side for your selected indicator type. While creating a new TI object, you can do TI object curation. This includes defining the relationship. You can also quickly duplicate TI objects, making it easier for those who create multiple TI objects daily. Please note that we also introduced an “Add and duplicate” button to allow customers to create multiple TI objects with the same metadata to streamline a manual bulk process. Demo 3: New supported IoC types The attack pattern builder now supports the creation of four new indicator types. These enable customers to build more specific attack patterns that boost understanding of and organizational knowledge around threats. These new indicators include: X509 certificate X509 certificates are used to authenticate the identity of devices and servers, ensuring secure communication over the internet. They are crucial in preventing man-in-the-middle attacks and verifying the legitimacy of websites and services. For instance, if a certificate is suddenly replaced or a new, unknown certificate appears, it could indicate a compromised server or a malicious actor attempting to intercept communications. JA3 JA3 fingerprints are unique identifiers generated from the TLS/SSL handshake process. They help in identifying specific applications and tools used in network traffic, making it easier to detect malicious activities For example, if a network traffic analysis reveals a JA3 fingerprint matching that of the Cobalt Strike tool, it could indicate an ongoing cyber attack. JA3S JA3S fingerprints extend the capabilities of JA3 by also including server-specific characteristics in the fingerprinting process. This provides a more comprehensive view of the network traffic and helps in identifying both client and server-side threats For instance, if a server starts communicating with an unknown external IP address using a specific JA3S fingerprint, it could be a sign of a compromised server or data exfiltration attempt. User agent User Agents provide information about the client software making requests to a server, such as the browser or operating system. They are useful in identifying and profiling devices and applications accessing a network For example, if a User Agent string associated with a known malicious browser extension appears in network logs, it could indicate a compromised device. Conclusion: The ability to ingest, curate, and establish relationships between various threat intelligence objects such as Threat Actors, Attack Patterns, and Identities provides a powerful framework for incident responders and threat intelligence analysts. The use of STIX objects not only improves interoperability and sharing of threat intelligence but also empowers organizations to hunt and investigate threats more efficiently. As customers adopt these new capabilities, they will find themselves better equipped to understand the full context of an attack and build robust defenses against future threats. With the public preview of Threat Intelligence (TI) object support, organizations are encouraged to explore these new tools and integrate them into their security operations, taking the first step towards a more informed and proactive approach to cybersecurity.Microsoft Sentinel’s AI-driven UEBA ushers in the next era of behavioral analytics
Co-author - Ashwin Patil Security teams today face an overwhelming challenge: every data point is now a potential security signal and SOCs are drowning in complex logs, trying to find the needle in the haystack. Microsoft Sentinel User and Entity Behavior Analytics (UEBA) brings the power of AI to automatically surface anomalous behaviors, helping analysts cut through the noise, save time, and focus on what truly matters. Microsoft Sentinel UEBA has already helped SOCs uncover insider threats, detect compromised accounts, and reveal subtle attack signals that traditional rule-based methods often miss. These capabilities were previously powered by a core set of high-value data sources - such as sign-in activity, audit logs, and identity signals - that consistently delivered rich context and accurate detections. Today, we’re excited to announce a major expansion: Sentinel UEBA now supports six new data sources including Microsoft first- and third-party platforms like Azure, AWS, GCP, and Okta, bringing deeper visibility, broader context, and more powerful anomaly detection tailored to your environment. This isn’t just about ingesting more logs. It’s about transforming how SOCs understand behavior, detect threats, and prioritize response. With this evolution, analysts gain a unified, cross-platform view of user and entity behavior, enabling them to correlate signals, uncover hidden risks, and act faster with greater confidence. Newly supported data sources are built for real-world security use cases: Authentication activities MDE DeviceLogonEvents – Ideal for spotting lateral movement and unusual access. AADManagedIdentitySignInLogs – Critical for spotting stealthy abuse of non - human identities. AADServicePrincipalSignInLogs - Identifying anomalies in service principal usage such as token theft or over - privileged automation. Cloud platforms & identity management AWS CloudTrail Login Events - Surfaces risky AWS account activity based on AWS CloudTrail ConsoleLogin events and logon related attributes. GCP Audit Logs - Failed IAM Access, Captures denied access attempts indicating reconnaissance, brute force, or privilege misuse in GCP. Okta MFA & Auth Security Change Events – Flags MFA challenges, resets, and policy modifications that may reveal MFA fatigue, session hijacking, or policy tampering. Currently supports the Okta_CL table (unified Okta connector support coming soon). These sources feed directly into UEBA’s entity profiles and baselines - enriching users, devices, and service identities with behavioral context and anomalies that would otherwise be fragmented across platforms. This will complement our existing supported log sources - monitoring Entra ID sign-in logs, Azure Activity logs and Windows Security Events. Due to the unified schema available across data sources, UEBA enables feature-rich investigation and the capability to correlate across data sources, cross platform identities or devices insights, anomalies, and more. AI-powered UEBA that understands your environment Microsoft Sentinel UEBA goes beyond simple log collection - it continuously learns from your environment. By applying AI models trained on your organization’s behavioral data, UEBA builds dynamic baselines and peer groups, enabling it to spot truly anomalous activity. UBEA builds baselines from 10 days (for uncommon activities) to 6 months, both for the user and their dynamically calculated peers. Then, insights are surfaced on the activities and logs - such as an uncommon activity or first-time activity - not only for the user but among peers. Those insights are used by an advanced AI model to identify high confidence anomalies. So, if a user signs in for the first time from an uncommon location, a common pattern in the environment due to reliance on global vendors, for example, then this will not be identified as an anomaly, keeping the noise down. However, in a tightly controlled environment, this same behavior can be an indication of an attack and will surface in the Anomalies table. Including those signals in custom detections can help affect the severity of an alert. So, while logic is maintained, the SOC is focused on the right priorities. How to use UEBA for maximum impact Security teams can leverage UEBA in several key ways. All the examples below leverage UEBA’s dynamic behavioral baselines looking back up to 6 months. Teams can also leverage the hunting queries from the "UEBA essentials" solution in Microsoft Sentinel's Content Hub. Behavior Analytics: Detect unusual logon times, MFA fatigue, or service principal misuse across hybrid environments. Get visibility into geo-location of events and Threat Intelligence insights. Here’s an example of how you can easily discover Accounts authenticating without MFA and from uncommonly connected countries using UEBA behaviorAnalytics table: BehaviorAnalytics | where TimeGenerated > ago(7d) | where EventSource == "AwsConsoleSignIn" | where ActionType == "ConsoleLogin" and ActivityType == "signin.amazonaws.com" | where ActivityInsights.IsMfaUsed == "No" | where ActivityInsights.CountryUncommonlyConnectedFromInTenant == True | evaluate bag_unpack(UsersInsights, "AWS_") | where InvestigationPriority > 0 // Filter noise - uncomment if you want to see low fidelity noise | project TimeGenerated, _WorkspaceId, ActionType, ActivityType, InvestigationPriority, SourceIPAddress, SourceIPLocation, AWS_UserIdentityType, AWS_UserIdentityAccountId, AWS_UserIdentityArn Anomaly detection Identify lateral movement, dormant account reactivation, or brute-force attempts, even when they span cloud platforms. Below are examples of how to discover UEBA Anomalous AwsCloudTrail anomalies via various UEBA activity insights or device insights attributes: Anomalies | where AnomalyTemplateName in ( "UEBA Anomalous Logon in AwsCloudTrail", // AWS ClousTrail anomalies "UEBA Anomalous MFA Failures in Okta_CL", "UEBA Anomalous Activity in Okta_CL", // Okta Anomalies "UEBA Anomalous Activity in GCP Audit Logs", // GCP Failed IAM access anomalies "UEBA Anomalous Authentication" // For Authentication related anomalies ) | project TimeGenerated, _WorkspaceId, AnomalyTemplateName, AnomalyScore, Description, AnomalyDetails, ActivityInsights, DeviceInsights, UserInsights, Tactics, Techniques Alert optimization Use UEBA signals to dynamically adjust alert severity in custom detections—turning noisy alerts into high-fidelity detections. The example below shows all the users with anomalous sign in patterns based on UEBA. Joining the results with any of the AWS alerts with same AWS identity will increase fidelity. BehaviorAnalytics | where TimeGenerated > ago(7d) | where EventSource == "AwsConsoleSignIn" | where ActionType == "ConsoleLogin" and ActivityType == "signin.amazonaws.com" | where ActivityInsights.FirstTimeConnectionViaISPInTenant == True or ActivityInsights.FirstTimeUserConnectedFromCountry == True | evaluate bag_unpack(UsersInsights, "AWS_") | where InvestigationPriority > 0 // Filter noise - uncomment if you want to see low fidelity noise | project TimeGenerated, _WorkspaceId, ActionType, ActivityType, InvestigationPriority, SourceIPAddress, SourceIPLocation, AWS_UserIdentityType, AWS_UserIdentityAccountId, AWS_UserIdentityArn, ActivityInsights | evaluate bag_unpack(ActivityInsights) Another example shows anomalous key vault access from service principal with uncommon source country location. Joining this activity with other alerts from the same service principle increases fidelity of the alerts. You can also join the anomaly UEBA Anomalous Authentication with other alerts from the same identity to bring the full power of UEBA into your detections. BehaviorAnalytics | where TimeGenerated > ago(1d) | where EventSource == "Authentication" and SourceSystem == "AAD" | evaluate bag_unpack(ActivityInsights) | where LogonMethod == "Service Principal" and Resource == "Azure Key Vault" | where ActionUncommonlyPerformedByUser == "True" and CountryUncommonlyConnectedFromByUser == "True" | where InvestigationPriority > 0 Final thoughts This release marks a new chapter for Sentinel UEBA—bringing together AI, behavioral analytics, and cross-cloud and identity management visibility to help defenders stay ahead of threats. If you haven’t explored UEBA yet, now’s the time. Enable it in your workspace settings and don’t forget to enable anomalies as well (in Anomalies settings). And if you’re already using it, these new sources will help you unlock even more value. Stay tuned for our upcoming Ninja show and webinar (register at aka.ms/secwebinars), where we’ll dive deeper into use cases. Until then, explore the new sources, use the UEBA workbook, update your watchlists, and let UEBA do the heavy lifting. UEBA onboarding and setting documentation Identify threats using UEBA UEBA enrichments and insights reference UEBA anomalies referenceAutomating Microsoft Sentinel: Part 2: Automate the mundane away
Welcome to the second entry of our blog series on automating Microsoft Sentinel. In this series, we’re showing you how to automate various aspects of Microsoft Sentinel, from simple automation of Sentinel Alerts and Incidents to more complicated response scenarios with multiple moving parts. So far, we’ve covered Part 1: Introduction to Automating Microsoft Sentinel where we talked about why you would want to automate as well as an overview of the different types of automation you can do in Sentinel. Here is a preview of what you can expect in the upcoming posts [we’ll be updating this post with links to new posts as they happen]: Part 1: Introduction to Automating Microsoft Sentinel Part 2: Automation Rules [You are here] – Automate the mundane away Part 3: Playbooks 1 – Playbooks Part I – Fundamentals Part 4: Playbooks 2 – Playbooks Part II – Diving Deeper Part 5: Azure Functions / Custom Code Part 6: Capstone Project (Art of the Possible) – Putting it all together Part 2: Automation Rules – Automate the mundane away Automation rules can be used to automate Sentinel itself. For example, let’s say there is a group of machines that have been classified as business critical and if there is an alert related to those machines, then the incident needs to be assigned to a Tier 3 response team and the severity of the alert needs to be raised to at least “high”. Using an automation rule, you can take one analytic rule, apply it to the entire enterprise, but then have an automation rule that only applies to those business-critical systems to make those changes. That way only the items that need that immediate escalation receive it, quickly and efficiently. Automation Rules In Depth So, now that we know what Automation Rules are, let’s dive in to them a bit deeper to better understand how to configure them and how they work. Creating Automation Rules There are three main places where we can create an Automation Rule: 1) Navigating to Automation under the left menu 2) In an existing Incident via the “Actions” button 3) When writing an Analytic Rule, under the “Automated response” tab The process for each is generally the same, except for the Incident route and we’ll break that down more in a bit. When we create an Automation Rule, we need to give the rule a name. It should be descriptive and indicative of what the rule is going to do and what conditions it applies to. For example, a rule that automatically resolves an incident based on a known false positive condition on a server named SRV02021 could be titled “Automatically Close Incident When Affected Machine is SRV02021” but really it’s up to you to decide what you want to name your rules. Trigger The next thing we need to define for our Automation Rule is the Trigger. Triggers are what cause the automation rule to begin running. They can fire when an incident is created or updated, or when an alert is created. Of the two options (incident based or alert based), it’s preferred to use incident triggers as they’re potentially the aggregation of multiple alerts and the odds are that you’re going to want to take the same automation steps for all of the alerts since they’re all related. It’s better to reserve alert-based triggers for scenarios where an analytic rule is firing an alert, but is set to not create an incident. Conditions Conditions are, well, the conditions to which this rule applies. There are two conditions that are always present: The Incident provider and the Analytic rule name. You can choose multiple criterion and steps. For example, you could have it apply to all incident providers and all rules (as shown in the picture above) or only a specific provider and all rules, or not apply to a particular provider, etc. etc. You can also add additional Conditions that will either include or exclude the rule from running. When you create a new condition, you can build it out by multiple properties ranging from information about the Incident all the way to information about the Entities that are tagged in the incident Remember our earlier Automation Rule title where we said this was a false positive about a server name SRV02021? This is where we make the rule match that title by setting the Condition to only fire this automation if the Entity has a host name of “SRV2021” By combining AND and OR group clauses with the built in conditional filters, you can make the rule as specific as you need it to be. You might be thinking to yourself that it seems like while there is a lot of power in creating these conditions, it might be a bit onerous to create them for each condition. Recall earlier where I said the process for the three ways of creating Automation Rules was generally the same except using the Incident Action route? Well, that route will pre-fill variables for that selected instance. For example, for the image below, the rule automatically took the rule name, the rules it applies to as well as the entities that were mapped in the incident. You can add, remove, or modify any of the variables that the process auto-maps. NOTE: In the new Unified Security Operations Platform (Defender XDR + Sentinel) that has some new best practice guidance: If you've created an automation using "Title" use "Analytic rule name" instead. The Title value could change with Defender's Correlation engine. The option for "incident provider" has been removed and replaced by "Alert product names" to filter based on the alert provider. Actions Now that we’ve tuned our Automation Rule to only fire for the situations we want, we can now set up what actions we want the rule to execute. Clicking the “Actions” drop down list will show you the options you can choose When you select an option, the user interface will change to map to your selected option. For example, if I choose to change the status of the Incident, the UX will update to show me a drop down menu with options about which status I would like to set. If I choose other options (Run playbook, change severity, assign owner, add tags, add task) the UX will change to reflect my option. You can assign multiple actions within one Automation Rule by clicking the “Add action” button and selecting the next action you want the system to take. For example, you might want to assign an Incident to a particular user or group, change its severity to “High” and then set the status to Active. Notably, when you create an Automation rule from an Incident, Sentinel automatically sets a default action to Change Status. It sets the automation up to set the Status to “Closed” and a “Benign Positive – Suspicious by expected”. This default action can be deleted and you can then set up your own action. In a future episode of this blog we’re going to be talking about Playbooks in detail, but for now just know that this is the place where you can assign a Playbook to your Automation Rules. There is one other option in the Actions menu that I wanted to specifically talk about in this blog post though: Incident Tasks Incident Tasks Like most cybersecurity teams, you probably have a run book of the different tasks or steps that your analysts and responders should take for different situations. By using Incident Tasks, you can now embed those runbook steps directly in the Incident. Incident tasks can be as lightweight or as detailed as you need them to be and can include rich formatting, links to external content, images, etc. When an incident with Tasks is generated, the SOC team will see these tasks attached as part of the Incident and can then take the defined actions and check off that they’ve been completed. Rule Lifetime and Order There is one last section of Automation rules that we need to define before we can start automating the mundane away: when should the rule expire and in what order should the rule run compared to other rules. When you create a rule in the standalone automation UX, the default is for the rule to expire at an indefinite date and time in the future, e.g. forever. You can change the expiration date and time to any date and time in the future. If you are creating the automation rule from an Incident, Sentinel will automatically assume that this rule should have an expiration date and time and sets it automatically to 24 hours in the future. Just as with the default action when created from an incident, you can change the date and time of expiration to any datetime in the future, or set it to “Indefinite” by deleting the date. Conclusion In this blog post, we talked about Automation Rules in Sentinel and how you can use them to automate mundane tasks in Sentinel as well as leverage them to help your SOC analysts be more effective and consistent in their day-to-day with capabilities like Incident Tasks. Stay tuned for more updates and tips on automating Microsoft Sentinel!Automating Microsoft Sentinel: Playbook Fundamentals
Welcome to the third entry of our blog series on automating Microsoft Sentinel. In this series, we’re showing you how to automate various aspects of Microsoft Sentinel, from simple automation of Sentinel Alerts and Incidents to more complicated response scenarios with multiple moving parts. So far, we’ve covered Part 1: Introduction to Automating Microsoft Sentinel where we talked about why you would want to automate as well as an overview of the different types of automation you can do in Sentinel and Part 2: Automation Rules where we talked about automating the mundane away. In this post, we’re going to start talking about Playbooks which can be used for automating just about anything. Here is a preview of what you can expect in the upcoming posts [we’ll be updating this post with links to new posts as they happen]: Part 1: Introduction to Automating Microsoft Sentinel Part 2: Automation Rules – Automate the mundane away Part 3: Playbooks 1 Part I – Fundamentals [You are here] Part 4: Playbooks 2 Part II – Diving Deeper Part 5: Azure Functions / Custom Code Part 6: Capstone Project (Art of the Possible) – Putting it all together Part 3: Playbooks - Fundamentals Pre-Built Playbooks in Content Hub Before we dive any deeper into Playbooks, I want to first point out that there are many pre-built playbooks available in the Content Hub. As of this writing, there are 484 playbooks available from 195 providers covering all manner of use cases like threat intelligence ingestion, incident response, operations integrations, and more in both first party Microsoft and third-party security tools. Before we dive into the internals of Playbooks and start creating our own, you really should do yourself a favor and take a look at the Content Hub and see if there isn’t already a Playbook doing what you want. You can also review the list of solutions at the Microsoft Sentinel GitHub page at Azure-Sentinel/Solutions at master · Azure/Azure-Sentinel Basic Structure of a Playbook Microsoft Sentinel Playbooks are built on Azure Logic Apps which is a low to no-code workflow automation platform. We’ll be diving into the details of how to create a Logic App from start to finish in the next installment of this series, but for now just know that there are two key “custom” features that Sentinel exposes for use in Playbooks: Triggers and Entities. Triggers The events or actions that can start a Playbook running are Triggers. These can be Incident, Alert, or Entity based. Incident Triggers Incident triggers are when an incident is either created or updated in Sentinel. Incident triggers can be tied to Automation Rules (which were covered in part 2 of this series) and can also be manually triggered by an analyst. Playbooks launched with Incident triggers receive all the incident objects, including any entities it contains as well as the alerts it is comprised of. Alert Triggers Alert triggers are similar to Incident triggers; except they trigger when an Alert is fired due to an Analytic Rule having a result. This is especially useful when you have an Alert that is not configured to create an Incident. Alert triggers can also be tied to Automation Rules Entity Triggers Entity triggers are different from Incident and Alert triggers as they cannot be tied to Automation Rules. Instead, they are triggered manually by an analyst. For example, let’s say that there is a user account that is part of an Incident and during the investigation the analyst decided they wanted to disable that user account in Entra. They could use an Entity Trigger to launch the Playbook, passing the Account Entity to the playbook for the account to be disabled. Entities We can’t really talk about Entity Triggers without talking about Entities themselves. So, what is an Entity in Sentinel? Entities are data elements that identify components in an alert or incident. There are many different types of entities within Sentinel, but for Playbooks we only need to focus on five key ones: IP Host Account URL FileHash (for more information on Entities in general, please see: https://learn.microsoft.com/azure/sentinel/entities ) How do you use Entity Triggers? When you are building an Analytic rule, you can identify the different Entities that it contains. These are then carried along as part of the Alert and exposed for further actions. This means that all you need to do is map the results of the Analytic Rule to the different Entity types using values returned from your query. For example, let’s say we are creating an Analytic Rule to alert on a new CloudShell user being created in Azure with the following query: let match_window = 3m; AzureActivity | where ResourceGroup has "cloud-shell" | where (OperationNameValue =~ "Microsoft.Storage/storageAccounts/listKeys/action") | where ActivityStatusValue =~ "Success" | extend TimeKey = bin(TimeGenerated, match_window), AzureIP = CallerIpAddress | join kind = inner (AzureActivity | where ResourceGroup has "cloud-shell" | where (OperationNameValue =~ "Microsoft.Storage/storageAccounts/write") | extend TimeKey = bin(TimeGenerated, match_window), UserIP = CallerIpAddress ) on Caller, TimeKey | summarize count() by TimeKey, Caller, ResourceGroup, SubscriptionId, TenantId, AzureIP, UserIP, HTTPRequest, Type, Properties, CategoryValue, OperationList = strcat(OperationNameValue, ' , ', OperationNameValue1) | extend Name = tostring(split(Caller,'@',0)[0]), UPNSuffix = tostring(split(Caller,'@',1)[0]) When we use this query as the basis for an Alert, we can then use Entity Mapping under Alert Enhancement to take the relevant fields returned and map them to Entity objects: This example maps the values "Caller", "Name", and "UPNSuffix" returned by the query to the "FullName", "Name", and "UPNSuffix" fields of an Account Entity. It also maps the UserIP result to the "Address" field of an IP Entity. When the Alert fires, it will include a collection of Account and IP Entities with the necessary values in its Entities field. Now if we wanted to, we could use a Playbook based on Entity Triggers to act on the Account or IP entities. What is a “strong” identifier versus a “weak” identifier and why is it important? Entities have fields that identify individual instances. Strong identifiers uniquely identify an entity, while weak identifiers may not. Often, combining weak identifiers can create a strong identifier. For example, Account entities can be identified by a strong identifier like a Microsoft Entra ID (GUID) or User Principal Name (UPN). Alternatively, a combination of weak identifiers like Name and NTDomain can be used. Different data sources might identify the same user differently. When Microsoft Sentinel recognizes two entities as the same based on their identifiers, it merges them into one for consistent handling. We’ll be covering more details on using Entities and Triggers in the next article when we start building Playbooks from scratch. Conclusion In this article we talked about the fundamentals of Playbooks in Sentinel , the Content Hub which is the home of pre-built Playbooks, as well as the different types of Triggers that can be used to launch a Playbook. In the next article we’ll be covering how to build a playbook from scratch and put these concepts to work. Additional Resources Supported triggers and actions in Microsoft Sentinel playbooks Entities in Microsoft SentinelManage cases from across tenants in one place
Are you managing the security needs of a large organization or a managed security service provider (MSSP)? Would you like a unified view of all the cases you are managing across these tenants? We are pleased to announce the latest addition to our case management solution, multi-tenant support, is now generally available (GA). This is the latest step in our journey towards providing a native, security-focused case management system that spans all SecOps workloads in the Microsoft Defender portal, removing customer reliance on third-party SIEM/XDR and ticketing systems. This capability is available for all Microsoft Sentinel customers that have onboarded to the Defender portal.Automating Microsoft Sentinel: A blog series on enabling Smart Security
Welcome to the first entry of our blog series on automating Microsoft Sentinel. We're excited to share insights and practical guidance on leveraging automation to enhance your security posture. In this series, we'll explore the various facets of automation within Microsoft Sentinel. Whether you're a seasoned security professional or just starting, our goal is to empower you with the knowledge and tools to streamline your security operations and stay ahead of threats. Join us on this journey as we uncover the power of automation in Microsoft Sentinel and learn how to transform your security strategy from reactive to proactive. Stay tuned for our upcoming posts where we'll dive deeper into specific automation techniques and share success stories from the field. Let's make your security smarter, faster, and more resilient together. In this series, we will show you how to automate various aspects of Microsoft Sentinel, from simple automation of Microsoft Sentinel Alerts and Incidents to more complicated response scenarios with multiple moving parts. We’re doing this as a series so that we can build up our knowledge step-by-step and finishing off with a “capstone project” that takes SOAR into areas that most people aren’t aware of or even thought was possible. Here is a preview of what you can expect in the upcoming posts [we’ll be updating this post with links to new posts as they happen]: Part 1: [You are here] – Introduction to Automating Microsoft Sentinel Part 2: Automation Rules – Automate the mundane away Part 3: Playbooks 1 – Playbooks Part I – Fundamentals o Triggers o Entities o In-App Content / GitHub o Consumption plan vs. dedicated – which to choose and why? Part 4: Playbooks 2 – Playbooks Part II – Diving Deeper o Built-In 1 st and 3 rd Party Connections (ServiceNow, etc.) o REST APIs (everything else) Part 5: Azure Functions / Custom Code o Why Azure Functions? o Consumption vs. Dedicated – which to choose and why? Part 6: Capstone Project (Art of the Possible) – Putting it all together Part 1: Introduction to Automating Microsoft Sentinel Microsoft Sentinel is a cloud-native security information and event management (SIEM) platform that helps you collect, analyze, and respond to security threats across your enterprise. But did you know that it also has a native, integrated Security Orchestration, Automation, and Response (SOAR) platform? A SOAR platform that can do just about anything you can think of? It’s true! What is SOAR and why would I want to use it? A Security Orchestration, Automation, and Response (SOAR) platform helps your team take action in response to alerts or events in your SIEM. For example, let’s say Contoso Corp has a policy where if a user has a medium sign-in risk in Entra ID and fails their login three times in a row within a ten-minute timeframe that we force them to re-confirm their identity with MFA. While an analyst could certainly take the actions required, wouldn’t it be better if we could do that automatically? Using the Sentinel SOAR capabilities, you could have an analytic rule that automatically takes the action without the analyst being involved at all. Why Automate Microsoft Sentinel? Automation is a key component of any modern security operations center (SOC). Automation can help you: Reduce manual tasks and human errors Improve the speed and accuracy of threat detection and response Optimize the use of your resources and skills Enhance your visibility and insights into your security environment Align your security processes with your business objectives and compliance requirements Reduce manual tasks and human errors Alexander Pope famously wrote “To err is human; to forgive, divine”. Busy and distracted humans make mistakes. If we can reduce their workload and errors, then it makes sense to do so. Using automation, we can make sure that all of the proper steps in our response playbook are followed and we can make our analysts lives easier by giving them a simpler “point and click” response capability for those scenarios that a human is “in the loop” or by having the system run the automation in response to events and not have to wait for the analyst to respond. Improve the speed and accuracy of threat detection and response Letting machines do machine-like things (such as working twenty-four hours a day) is a good practice. Leveraging automation, we can let our security operations center (SOC) run around the clock by having automation tied to analytics. Rather than waiting for an analyst to come online, triage an alert and then take action, Microsoft Sentinel can stand guard and respond when needed. Optimize the use of your resources and skills Having our team members repeat the same mundane tasks is not optimal for the speed of response and their work satisfaction. By automating the mundane away, we can give our teams more time to learn new things or work on other tasks. Enhance your visibility and insights into your security environment Automation can be leveraged for more than just responding to an alert or incident. We can augment the information we have about entities involved in an alert or incident by using automation to call REST based APIs to do point-in-time lookups of the latest threat information, vulnerability data, patching statuses, etc. Align your security processes with your business objectives and compliance requirements If you have to meet particular regulatory requirements or internal KPIs, automation can help your team to achieve their goals quickly and consistently. What Tools and Frameworks Can You Use to Automate Microsoft Sentinel? Microsoft Sentinel provides several tools that enable you to automate your security workflows, such as: Automation Rules o Automation rules can be used to automate Microsoft Sentinel itself. For example, let’s say there is a group of machines that have been classified as business critical and if there is an alert related to those machines, then the incident needs to be assigned to a Tier 3 response team, and the severity of the alert needs to be raised to at least “high”. Using an automation rule, you can take one analytic rule, apply it to the entire enterprise, but then have an automation rule that only applies to those business-critical systems. That way only the items that need that immediate escalation receive it, quickly and efficiently. o Another great use of Automation Rules is to create Incident Tasks for analysts to follow. If you have a process and workflow, by using Incident Tasks, you can have those appear inside of an Incident right there for the analysts to follow. No need to go “look it up” in a PDF or other document. Playbooks: You can use playbooks to automatically execute actions based on triggers, such as alerts, incidents, or custom events. Playbooks are based on Azure Logic Apps, which allow you to create workflows using various connectors, such as Microsoft Teams, Azure Functions, Azure Automation, and third-party services. Azure Functions can be leveraged to run custom code like PowerShell or Python and can be called from Sentinel via Playbooks. This way if you have a process or code that’s beyond a Playbook , you can still call it from the normal Sentinel workflow. Conclusion In this blog post, we introduced the automation capabilities and benefits of SOAR in Microsoft Sentinel, and some of the tools and frameworks that you can use to automate your security workflows. In the next blog posts, we will dive deeper into each of these topics and provide some practical examples and scenarios of how to automate Microsoft Sentinel. Stay tuned for more updates and tips on automating Microsoft Sentinel! Additional Resources What are Automation Rules? Automate Threat Response with playbooks in Microsoft SentinelAnnouncing File Attachments for Case Management
Effective information sharing is crucial for resolving cases efficiently. Today, we are excited to announce the launch of File Attachments for Case Management, a capability designed to enhance your case investigations with the sharing of reports, emails, screenshots, log files, and more, all in one centralized location within a case. Key Benefits of Attachments for Case Management Centralized Information: File attachments ensure that all relevant documents, images, and data are stored in one place. Reduce your reliance on external file storage and stop hunting through emails—everything you need is right at your fingertips within the case. Comprehensive Documentation: From contracts and evidence to client communications and reports, file attachments provide a complete and organized record of all case-related materials. This comprehensive documentation is invaluable for audits, reviews, and future reference. More Accurate Response: Minimize errors and increase confidence in case outcomes by leveraging all relevant information related to a case. Comb over vulnerability assessments, patch documentation, configuration changes, etc. and ensure you have all the context you need about a case. Attachments Experience: The experience is super simple. Go to the Case details page, click the “Attachments” tab, click “Upload”, select your file, and wait for the upload. The file is malware scanned in the background. Once scanning is complete anyone with access to the case can download the file. If you need to upload malware samples, you can wrap them in password protected zip files. Q&A: How much file storage do I get? 500 GB. Do file attachments stay in region? Yes, they are stored in the same region as their tenant. What if I need to attach malware samples for case investigation? Zip and password protect your malware samples. Malware samples that have not been zipped and password protect will be removed by malware scan. Coming Soon! Add file attachments and screenshots directly to comments to quickly review attachments in the Activity Log. Conclusion Attachments for Case Management ensures you have all the necessary information to make quick and informed decisions about a case. This leads to better case outcomes and improved communication for your organization. Learn more Case management overview Case management blog postAnnouncing Rich Text for Case Management
We are excited to announce the public preview of Rich Text for Case Management. Clear and effective communication is critical for making fast and accurate decisions in case investigations. Learn more about how Rich Text can enhance your communication with your SOC team.
