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Hunting in Microsoft Sentinel allows security analysts to proactively search for potential security threats in their environment. While hunting queries provide insights into security events, analytical rules take the hunting capability to the next level. They allow security teams to automate the detection and response to security threats. This blog post will discuss the process of converting a hunting query to an analytical rule in Microsoft Sentinel.
Step 1: Create a Hunting Query
The first step in creating an analytical rule is to create a hunting query. A hunting query is a customized search for security events that matches specific criteria. Hunting queries can be used to investigate security incidents, identify emerging threats, and improve overall security posture. In Microsoft Sentinel, hunting queries are created using the Kusto Query Language (KQL).
Step 2: Refine the Query
Once a hunting query is created, it should be refined to ensure it meets the specific requirements for an analytical rule. This includes:
Refining the search criteria to ensure it only returns relevant results.
Narrowing the time range to ensure the query is only searching for recent events.
Ensuring the query is fast and efficient to prevent performance issues.
Step 3: Create an Analytical Rule
To create an analytical rule, go to the Microsoft Sentinel portal and navigate to Analytics. Then click on the Create button and select Scheduled Query Rule.
Step 4: Configure the Rule
The next step is to configure the analytical rule by completing the following steps:
Name the rule.
Define the scope of the rule.
Define the query schedule.
Add the KQL query created in Step 2.
Define the alert threshold and suppression settings.
Define the action to be taken when the rule is triggered.
Step 5: Test the Rule
Before enabling the rule, it is important to test it to ensure it is functioning as expected. This can be done by running the query and verifying that the results are accurate.
Step 6: Enable the Rule
After testing, the rule can be enabled by clicking the Enable Rule button.
Step 7: Monitor the Rule
Once the rule is enabled, it is important to monitor it to ensure it is functioning correctly. This can be done by checking the rule status in the Microsoft Sentinel portal and reviewing the alerts generated by the rule.
Converting a hunting query to an analytical rule allows security teams to automate the detection and response to security threats. By following the steps outlined in this blog post, security analysts can convert their hunting queries to analytical rules and improve their overall security posture in Microsoft Sentinel.
Azure Sentinel is a cloud-based security information and event management (SIEM) service provided by Microsoft. Its primary purpose is to help security professionals identify and respond to security threats and incidents.
A custom analytics rule is a security rule that you can create and customize to monitor your Azure Sentinel environment for specific security events. You can use custom analytics rules to detect and respond to security threats that are specific to your organization.
You can create a custom analytics rule in Azure Sentinel by first defining the query that will be used to detect the security event you are interested in, and then configuring the rule to trigger when that event is detected.
A scheduled query is a query that is run automatically on a regular schedule. In Azure Sentinel, you can use scheduled queries to monitor your environment for specific security events and trigger custom analytics rules when those events are detected.
Kusto is the query language used in Azure Sentinel. The syntax for a Kusto query includes keywords, operators, and functions that can be used to filter, aggregate, and transform data. Kusto queries can be used in Azure Sentinel to identify and analyze security events.
You can test a custom analytics rule in Azure Sentinel by running a sample query and verifying that the rule is triggered as expected. You can also use the Query explorer in Azure Sentinel to visualize the results of your query and verify that the data matches your expectations.
Query result aggregation is the process of grouping query results based on specific criteria, such as a particular field or time range. In Azure Sentinel, you can use query result aggregation to visualize and analyze security events, and to trigger custom analytics rules based on specific aggregation criteria.
You can configure a custom analytics rule in Azure Sentinel to send an alert when a security event is detected by setting up an alert rule that is triggered by the custom analytics rule. You can also specify the notification channels and severity levels for the alert.
You can use the Azure Sentinel Workspace to view and analyze security events by using the built-in dashboards and visualizations, such as the Overview dashboard and the Incident Management dashboard. You can also create custom dashboards and visualizations based on your specific security needs.
The benefits of using Azure Sentinel for security monitoring and threat detection include its ability to aggregate and analyze large volumes of security data, its integration with Microsoft and third-party security solutions, and its customizable and extensible analytics and alerting capabilities.
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