As such, a deep understanding of how to convert a hunting query to an analytical rule is imperative. This knowledge can aid security analysts in both identifying and responding to potential security threats more efficiently.
What Is a Hunting Query
A hunting query in simple terms is an investigative query typically used to explore data in-depth to identify suspicious activities. This generally involves a proactive approach, using educated hypotheses, to search across collected data in order to find hidden threats. It uses Kusto Query Language (KQL) to perform these investigations, probing data from various sources such as logs and telemetry data.
What Is an Analytical Rule
Analytical rules, on the other hand, are pre-defined rules that automatically scan for potential threats based on set parameters and conditions. These rules can trigger alerts when certain criteria are met. Essentially, they help to automate the process of threat detection, thereby alleviating the need for manual queries. Analytical rules also use KQL for defining the rule conditions.
Converting Hunting Query to Analytical Rule
Microsoft’s Azure Sentinel provides a cost-effective and efficient platform to convert hunting queries into analytical rules. To implement this, follow the steps outlined below:
- Navigate to Azure Sentinel Solutions: In the Azure portal, locate Azure Sentinel and navigate to the
Huntingmenu. - Choose the Required Query: Select the query you wish to convert into an analytical rule and click on the three dots (‘…’) to view more options.
- Create New Rule: Click on
New Rule. This will direct you to the ‘Analytics rule wizard’ page. - Fill in the Essential Details: You will be required to fill in the essential details for the rule including the Rule name, Tactics, Severity, Status, Suppression duration, Rule logic, etc.
- Review & Create: Review the details and hit
Create. This will create a new rule based on the hunting query you selected earlier.
Sample Conversion Example
Let’s take an example of a hunting query that identifies if any account is trying to modify other users’ properties in Office 365.
Hunting Query Example:
OfficeActivity
| where Operation =~ 'Set-Mailbox'
| extend ModifiedProperties = parse_json(ModifiedProperties)
| mv-expand ModifiedProperties
| where ModifiedProperties.Name contains "RoleAssignmentPolicy"
| summarize count() by UserIds, UserId = tostring(UserId), EntityId = MailboxOwnerUPN, OfficeObjectId = MailboxOwnerUPN
To convert this to an analytical rule in Azure Sentinel, you would follow the steps outlined above, inputting the exact query in the ‘New Rule’ section.
Remember, when converting hunting queries to analytical rules, the required outcome is an automated system that identifies and alerts you of potential threats based on the original conditions specified in the hunting query.
Conclusion
Converting hunting queries into analytical rules is an integral part of a Security Operations Analyst’s role when using tools like Azure Sentinel. The transition from a proactive, hypothesis-driven approach of hunting queries to the automated, alerting approach offered by analytical rules is a critical component in maintaining a robust and efficient security infrastructure.
Practice Test
True or False: Hunting query and analytical rule are the same thing in Microsoft Azure Sentinel.
- True
- False
Answer: False.
Explanation: Hunting query and analytical rule serve different purposes in Azure Sentinel. A hunting query is a proactive technique to discover potential threats, while an analytical rule is used to create incident alerts based on certain conditions.
In Azure Sentinel, analytical rules can be created from saved Hunting queries.
- True
- False
Answer: True.
Explanation: Azure Sentinel allows users to create analytical rules from saved hunting queries. This makes it easier to operationalize your hunting knowledge.
True or False: ‘Hunting’ is a responsive approach in cybersecurity where analysts respond to alerts.
- True
- False
Answer: False.
Explanation: ‘Hunting’ is a proactive approach in Azure Sentinel where analysts proactively search for security threats that might not be picked up by automated security systems.
Which of the following steps are essential to convert a hunting query to an analytical rule in Azure Sentinel? (Choose all that apply)
- A. Save the Hunting query
- B. Define rule logic
- C. Select ‘Convert to analytics rule’
- D. Test the rule
Answer: A, B, C, D
Explanation: All these steps are crucial while converting a hunting query to an analytical rule in Azure Sentinel. The conversion involves saving the query, defining the rule logic, selecting ‘Convert to analytics rule’, and testing the rule.
What language is used to write hunting queries in Azure Sentinel?
- A. Python
- B. JavaScript
- C. Kusto Query Language (KQL)
- D. SQL
Answer: C. Kusto Query Language (KQL)
Explanation: Hunting queries in Azure Sentinel are written using Kusto Query Language (KQL).
True or False: Analytical rules in Azure Sentinel are created to set up automatic alerts for potential threats.
- True
- False
Answer: True.
Explanation: Analytical rules are created in Azure Sentinel to automate detection and provide alerts on potential security threats based on the conditions defined in the rule.
True or False: You can convert an analytical rule back into a hunting query.
- True
- False
Answer: False.
Explanation: Azure Sentinel allows you to convert a hunting query into an analytical rule, but not vice-versa.
What is the primary benefit of converting a hunting query to an analytical rule in Azure Sentinel?
- A. Increase in query speed
- B. Automation of threat detection
- C. Better visualization of data
- D. Improvement in data storage
Answer: B. Automation of threat detection
Explanation: The primary benefit of converting a hunting query to an analytical rule is to automate threat detection, making the process more efficient.
True or False: In Microsoft Security Operations, a hunting query can only be converted into an analytics rule manually.
- True
- False
Answer: False.
Explanation: In Microsoft Security Operations, you can either manually convert a hunting query into an analytics rule or you can automate the process with the use of built-in tools.
In the process of converting a hunting query to an analytical rule, what is the role of the “Rule logic” section?
- A. Defining the query’s parameters
- B. Scheduling the query execution
- C. Creating a name for the analytical rule
- D. Defining the conditions when the rule generates an alert
Answer: D. Defining the conditions when the rule generates an alert
Explanation: In the “Rule logic” section, you specify the conditions under which the analytical rule should generate an alert based on the hunting query.
Interview Questions
What is the primary purpose of converting a hunting query into an analytical rule in Microsoft security operations?
Converting a hunting query into an analytical rule allows you to automate the process of identifying and investigating potential security threats, thereby improving efficiency and response time.
What is a hunting query in the realm of Microsoft security operations?
A hunting query is a proactive search through data in an effort to find security threats that automated tools might have missed. They are custom-built investigations by security professionals.
How do you convert a hunting query to an analytical rule in Microsoft Defender for Endpoint?
To convert a hunting query to an analytical rule, you need to open Microsoft Defender Security Center and navigate to the ‘Advanced Hunting’ section. After selecting the query you want to convert, you’ll click on ‘Convert to detection rule’.
How can converting a hunting query into an analytical rule improve the performance of Microsoft Defender?
By converting a hunting query to an analytic rule, Microsoft Defender can constantly monitor and notify about potential threats that match that query. This proactive stance improves the overall performance of the platform.
What language is used to write hunting queries for Microsoft Security Operations?
The language used to write hunting queries is Kusto Query Language (KQL).
What capabilities does a converted analytical rule provide that a standard hunting query does not?
Unlike a standard hunting query, a converted analytical rule runs automatically at regular intervals, reducing the need for manual investigation. It also allows for alert settings and automatic responses when rule conditions are met.
What role does Microsoft Sentinel play in the process of converting hunting queries into analytical rules?
Microsoft Sentinel plays a key role in managing and handling hunting queries. It’s the platform where you convert these hunting queries into analytical rules and automate your threat response.
What’s the benefit of regular interval checks when a hunting query is converted to an analytical rule?
Regular interval checks can help quickly identify any unusual or suspicious activity matching the rule conditions, which can lead to faster discovery and remediation of potential security incidents.
Can you modify an analytical rule once it is converted from a hunting query in Microsoft Security Operations?
Yes, you can modify an analytical rule after it’s been converted from a hunting query. This includes altering the conditions of the rule, its actions upon triggering, and other settings.
How is an alert generated from an analytical rule based on a converted hunting query?
Once the conditions of an analytical rule are met, Microsoft Security Operations triggers an alert. This alert will appear in the platform’s console and can be set to notify the security team or trigger automated responses.
Can an analytical rule converted from a hunting query run on a specific schedule?
Yes, you can set an analytical rule converted from a hunting query to run at specific intervals or times. This is beneficial for targeting peak activity times or scheduling during low-traffic periods to lessen system impact.
What types of data can be analyzed by a hunting query or an analytical rule?
Both hunting queries and analytical rules can analyze data from various sources including logs, events, and alerts gathered from services like Microsoft Defender for Endpoint, Azure Security Center, and Microsoft 365 Defender.
Who is best suited to create and convert hunting queries into analytical rules?
Security analysts or professionals with knowledge of Kusto Query Language (KQL) are best suited to create and convert hunting queries into analytical rules.
What permissions are required to convert hunting queries into analytical rules in Microsoft Defender for Endpoint?
Permissions to manage security settings or global administrator permissions are required to convert hunting queries into analytical rules.
Are there predefined hunting queries that can be converted into analytical rules in Microsoft Defender?
Yes, Microsoft Defender for Endpoint offers a variety of prebuilt hunting queries that can be converted into analytical rules. However, custom hunting queries are often used for more specific or complex scenarios.
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