Tutorial / Cram Notes
Monitoring Azure Active Directory (Azure AD) is essential for maintaining the security and availability of your organization’s identity and access management infrastructure. By using Azure Monitor Log Analytics, administrators can track activities, detect potential security incidents, and ensure that Azure AD is functioning as expected. This involves the collection of logs, analyzing them using KQL (Kusto Query Language), and then interpreting the results to make informed decisions.
Collecting Azure AD Logs
To monitor Azure AD with Log Analytics, you must first ensure that activity logs are being collected. Azure AD provides several types of logs that can be ingested into Azure Monitor Log Analytics:
- Sign-in logs – Information about sign-ins and how your resources are accessed.
- Audit logs – Data that shows the history of changes applied to resources within Azure AD.
- Provisioning logs – Record of synchronization activities between Azure AD and other services.
- Risk detection and risky user logs – Security logs containing potential threat activities.
You can forward these logs to Azure Monitor by enabling the diagnostic settings in Azure AD. This allows you to send the logs to a Log Analytics workspace, where they will be stored and made available for analysis.
Analyzing Logs with KQL
Once data is collected in Log Analytics, you can use Kusto Query Language (KQL) to filter, sort, and analyze that data. KQL is a powerful language that allows for complex analytics and aggregations based on your specific needs.
Example Queries
Here are some example KQL queries that you might use to track activities in Azure AD:
– Query to retrieve sign-in logs:
SigninLogs
| where TimeGenerated > ago(1d)
This retrieves sign-in logs from the last day, helping you monitor recent activity.
– Query to examine risky sign-ins:
SigninLogs
| where RiskLevel during (high, medium)
| project TimeGenerated, UserPrincipalName, Location, RiskDetail, RiskLevel
This will list sign-ins that were flagged as high or medium risk, focusing on the most critical events.
– Query to filter logins by a specific user:
SigninLogs
| where UserPrincipalName == “user@example.com”
Using this query can help you track the sign-in patterns for a specific user account.
– Query to count the sign-in activities per application:
SigninLogs
| summarize Count = count() by AppDisplayName
| order by Count desc
This query will summarize the number of sign-in activities by application, providing insights into which apps are most used.
Interpreting Query Results
The results of your KQL queries provide a wealth of data that can be insightful and actionable. For example:
- An unexpected spike in sign-in failures might indicate a brute force attack.
- Sign-ins from unusual locations could suggest compromised credentials.
- High-risk login attempts might warrant immediate attention and potential remediation.
Alerting based on Log Analysis
Setting up alerts based on specific events or thresholds detected in your log data can further enhance monitoring. Azure Monitor provides the capability to create alert rules from the results of KQL queries. For instance:
- You can create an alert to notify your security team if there is an abnormal number of failed login attempts within a short time frame.
- Alerts can also be set for when new users are granted administrator roles, enabling you to quickly review and validate these changes.
Comparison of Monitoring Approaches
Aspect | Azure AD Portal | Azure Monitor Log Analytics |
---|---|---|
Accessibility | Direct via Azure portal | Requires querying with KQL |
Data Retention | Limited based on the Azure AD license | Customizable retention policies |
Query Flexibility | Standard views and filters | Advanced analysis with custom querying |
Alerting Capabilities | Basic alerts based on pre-defined categories | Advanced alerting based on KQL queries |
Data Aggregation | Basic aggregation capabilities | Extensive aggregation using KQL functions |
Integration | Integrated with Azure services | Can be integrated with other Azure monitoring tools |
Conclusion
Monitoring Azure AD with Azure Monitor Log Analytics provides a robust set of tools to secure and manage an organization’s identities. With the power of KQL, administrators can create precise queries to sift through vast amounts of log data, interpret patterns, set up alerts, and respond to potential security threats effectively. Understanding and using these capabilities are essential for anyone tasked with the responsibility of Azure AD management and security, such as those preparing for the SC-300 Microsoft Identity and Access Administrator exam.
Practice Test with Explanation
True/False: Azure Active Directory logs can be exported directly into Azure Log Analytics without any additional configuration.
- Answer: False
Explanation: Azure AD logs require additional configuration to be exported into Azure Log Analytics. You must first enable diagnostic settings and select the specific logs to send to your Log Analytics workspace.
True/False: KQL (Kusto Query Language) is the only query language supported by Azure Log Analytics.
- Answer: True
Explanation: KQL is the query language used by Azure Log Analytics to retrieve and analyze data.
Which of the following is a valid KQL operator for narrowing down a search in Log Analytics?
- A) where
- B) refine
- C) limit
- D) filter
- Answer: A) where
Explanation: The ‘where’ operator in KQL is used to filter search results based on specific conditions.
True/False: You can use KQL to create visualizations such as charts and graphs in Azure Log Analytics.
- Answer: True
Explanation: KQL supports creating visualizations directly within the query editor in Azure Log Analytics, which can be used for dashboards and reports.
In Azure Log Analytics, which of the following is a common table that stores Azure AD sign-in logs?
- A) ADActivity
- B) SigninLogs
- C) AADSignIns
- D) AADLogs
- Answer: B) SigninLogs
Explanation: The SigninLogs table in Azure Log Analytics stores Azure AD sign-in logs data.
True/False: Azure AD Audit Logs and Sign-in Logs are the same and stored in the same Log Analytics table.
- Answer: False
Explanation: Azure AD Audit Logs and Sign-in Logs are different. Sign-in Logs contain information about sign-in activities, while Audit Logs contain details on changes made within Azure AD. They are stored in separate tables.
Which of the following data can you obtain from the SigninLogs table in Azure Log Analytics? (Select all that apply)
- A) The user’s IP address
- B) The user’s password
- C) The application they signed into
- D) The user’s sign-in status
- Answer: A) The user’s IP address, C) The application they signed into, D) The user’s sign-in status
Explanation: The SigninLogs contain information like the user’s IP address, the application they signed in to, and the user’s sign-in status. It does not store passwords.
True/False: Azure AD logs in Log Analytics are retained indefinitely by default.
- Answer: False
Explanation: Azure AD logs are not retained indefinitely. Retention periods can be set in Log Analytics, and the default retention period is 30 days unless changed by the administrator.
To sort the results from a query in ascending order of a specific field, which KQL command should be used?
- A) sort asc
- B) orderby ascending
- C) sort by
- D) orderby
- Answer: D) orderby
Explanation: The ‘orderby’ command in KQL sorts the query results. You would append the field name and specify ‘asc’ for ascending or ‘desc’ for descending order.
True/False: Log Analytics can trigger alerts based on specific events in Azure AD logs.
- Answer: True
Explanation: Log Analytics can indeed trigger alerts based on specified events or criteria in Azure AD logs.
What is the purpose of the ‘distinct’ command in KQL?
- A) To remove duplicates from the results
- B) To select only a specific list of fields
- C) To count the number of distinct values
- D) To filter results based on a threshold
- Answer: A) To remove duplicates from the results
Explanation: The ‘distinct’ command in KQL is used to remove duplicate records from query results, showing only unique values for the selected fields.
True/False: It’s possible to query Azure AD logs in Log Analytics to investigate failed sign-ins.
- Answer: True
Explanation: You can query Azure AD logs in Log Analytics to investigate failed sign-ins by analyzing the SigninLogs table and filtering for records with sign-in errors.
Interview Questions
What is Log Analytics in Azure Active Directory?
Log Analytics is a service in Azure that helps collect and analyze data from various sources, including Azure Active Directory, to generate insights and actionable intelligence.
What is KQL?
KQL stands for Kusto Query Language, which is a query language used in Azure to query data in Log Analytics.
How do you install and use Log Analytics views in Azure AD?
To install and use Log Analytics views in Azure AD, you can follow the steps outlined in the documentation, which includes creating a Log Analytics workspace, connecting it to Azure AD, and creating custom views.
How can you connect Azure Active Directory to Azure Sentinel?
You can connect Azure Active Directory to Azure Sentinel by following the steps outlined in the documentation, which includes creating a workspace, configuring the data connector, and connecting to the Azure AD API.
What is Azure Sentinel?
Azure Sentinel is a cloud-native security information and event management (SIEM) service that helps you detect and respond to threats across your hybrid cloud and on-premises environments.
How can you set up alerts for activity logs in Azure Monitor?
You can set up alerts for activity logs in Azure Monitor by following the steps outlined in the documentation, which includes creating a new alert rule, defining the conditions and criteria, and specifying the notification actions.
What type of data can you collect from Azure Active Directory with Log Analytics?
You can collect a wide range of data from Azure Active Directory with Log Analytics, including sign-in data, audit logs, and user provisioning data.
How can KQL queries be used to monitor Azure AD?
KQL queries can be used to monitor Azure AD by analyzing the data collected from various sources and generating insights and actionable intelligence.
What is the purpose of Log Analytics workspaces in Azure AD?
The purpose of Log Analytics workspaces in Azure AD is to collect and store data from various sources, such as Azure Active Directory, and to provide tools for analyzing and visualizing that data.
How can Azure AD audit logs be used to detect security issues?
Azure AD audit logs can be used to detect security issues by tracking activities and events that may indicate a breach or unauthorized access, and by alerting security teams to potential threats.
What is the role of Azure Monitor in monitoring Azure AD?
Azure Monitor provides a centralized platform for monitoring and analyzing data from various sources, including Azure Active Directory, and for setting up alerts and notifications for security and performance issues.
What is the relationship between Log Analytics and Azure Sentinel?
Log Analytics and Azure Sentinel are closely related services in Azure that work together to collect, store, and analyze data from various sources to generate insights and detect security threats.
How can you use Log Analytics to track user activity in Azure AD?
You can use Log Analytics to track user activity in Azure AD by collecting sign-in data, audit logs, and other user-related data, and by analyzing that data using KQL queries and custom views.
What is the purpose of Azure AD Connect Health?
Azure AD Connect Health is a service that helps monitor and diagnose issues with the Azure AD Connect sync engine and the AD FS infrastructure.
What are some of the benefits of using Log Analytics to monitor Azure AD?
Some of the benefits of using Log Analytics to monitor Azure AD include improved visibility into user activity, better detection of security threats, and the ability to generate custom reports and insights.
This blog post on monitoring Azure AD with Log Analytics is fantastic! It’s super detailed and helpful. Thanks a lot!
Can somebody explain how to use KQL to filter Azure AD sign-in logs for just failed login attempts?
Sure, you can use the following KQL query: `SigninLogs | where ResultType != 0` to filter out only failed logins.
That’s correct! You can also add additional filters based on time or user for more specific results.
Great post! Using Log Analytics to monitor Azure AD is truly powerful. Thanks for sharing.
The KQL queries provided were spot on. I could immediately see where anomalous sign-ins were happening.
@User2 Totally agree! KQL is quite versatile.
I’m having a hard time understanding how to set up alerts based on these queries. Any suggestions?
@User4 Try creating an Azure Monitor alert rule using those KQL queries. It’s pretty straightforward once you get the hang of it.
@User4 You can also set thresholds in Log Analytics to trigger the alerts.
Thanks for the detailed explanation. It’s very helpful.
Anyone has tips for improving the performance of KQL queries?
@User8 Use ‘project’ and ‘summarize’ operators efficiently. Also, filter data as early as possible in the query.
@User8 Consider using ‘let’ statements to break complex queries into simpler parts.
Can we integrate these logs with other SIEM tools?
@User11 Yes, you can integrate Log Analytics with various SIEM solutions using connectors.
@User11 Azure Sentinel can be a good option for more advanced analytics and threat detection.