Automated Triage in Microsoft Sentinel

Microsoft Sentinel Automated Triage - Elevate your Security Posture
Andrew Posted on 8:00 am

Automated Triage in Microsoft Sentinel

In this post we will look at some different ways to automate incident triage in Microsoft Sentinel. Today, organizations face an ever-increasing volume of security threats. Cyberattacks are becoming more sophisticated, and the sheer number of alerts can overwhelm even the most seasoned security teams. Automated triage in Microsoft Sentinel emerges as a crucial solution, empowering organizations to respond swiftly and efficiently to potential threats.

This is where Microsoft Sentinel’s automated triage capabilities are a transformative solution that supports your SOC team to respond swiftly and efficiently to potential security incidents. By harnessing automation, artificial intelligence, and machine learning, automated triage in Microsoft Sentinel revolutionizes security operations, enabling teams to detect, prioritize, and respond to threats with unprecedented speed and accuracy.

Let’s dive into how automated triage can revolutionize your security operations together.

Understanding the Need for Automated Triage

Traditional security operations centers (SOCs) often struggle with:

  • Alert Fatigue: Thousands of alerts daily, many of which are false positives.
  • Limited Resources: Not enough analysts to manually investigate every alert.
  • Slow Response Times: Delays in identifying and responding to genuine threats.

Automated triage addresses these challenges by:

  • Prioritizing Threats: Automatically ranking alerts based on severity.
  • Accelerating Response: Initiating predefined actions without human intervention.
  • Enhancing Accuracy: Reducing false positives through intelligent analysis.

Core Components of Automated Triage in Microsoft Sentinel

AI and Machine Learning Analytics

At the heart of automated triage is the intelligent use of AI and machine learning. We want to focus on our core goals and identify specific tasks that we can evaluate for automation. Consider the following areas:

  • Anomaly Detection: AI models identify unusual patterns that may signify security breaches, such as atypical login attempts or data exfiltration activities.
    • Security Copilot is an excellent resource to utilize in this area with detections at the speed of compute.
  • Event Correlation: Machine learning correlates related alerts to reveal the full scope of an attack, connecting seemingly isolated incidents into a cohesive threat narrative.
  • False Positive Reduction: Continuous learning from past incidents refines the system’s ability to filter out irrelevant alerts, allowing security teams to focus on genuine threats.

Automation Rules

Automation rules streamline incident management by:

  • Defining Conditions and Actions: Set specific criteria for incidents (e.g., severity level, source) and corresponding automated actions.
  • Routing Incidents: Automatically assign incidents to the appropriate analyst or team based on predefined parameters.
  • Modifying Incident Properties: Dynamically update incident attributes like severity, status, or tags to reflect real-time analysis.

This automation reduces the manual workload on security personnel, ensuring a swift and standardized response to threats.

Playbooks with Azure Logic Apps

Playbooks are automated workflows built using Azure Logic Apps that:

  • Automate Responses: Execute predefined actions such as isolating compromised systems, blocking malicious IP addresses, or resetting user credentials.
  • Integrate with Third-Party Tools: Connect with ticketing systems, communication platforms, and other security solutions to coordinate comprehensive responses.
  • Ensure Consistency: Standardize procedures across the organization, minimizing the risk of oversight or human error during critical incidents.

By automating routine responses, playbooks free up analysts to focus on complex investigations and strategic initiatives. Automation Rules, playbooks, and logic apps (there are other methods available!) can all be used to provide Automated Triage and support rapid response to incidents in Microsoft Sentinel.

Setting Up Automated Triage: A Step-by-Step Guide

Implementing automated triage in Microsoft Sentinel is a strategic move that optimizes your security operations and enhances your team’s ability to respond to threats quickly and effectively. By automating routine tasks, your security team can focus on more complex and high-priority incidents

The steps below (1 through 4) will guide you through the process of setting up automated triage, from connecting your first data sources to configuring analytics rules and designing comprehensive playbooks.

This step-by-step walkthrough gives you a little exposure to the full potential of Microsoft Sentinel’s advanced capabilities, paving the way for your next steps towards further automations.

Prerequisites

Before you begin, ensure you have:

  • An Active Azure Subscription: With the necessary permissions to deploy and manage resources.
  • Microsoft Sentinel Workspace: Set up within your Azure environment.
  • Access to Data Sources: Such as Microsoft Entra ID, Office 365 Activity logs, Microsoft Defender XDR, firewalls, and other security logs.

1. Connecting Data Sources

The richness of your data sources directly impacts the effectiveness of threat detection.

  • Navigate to Data Connectors: In Microsoft Sentinel, go to Configuration > Data connectors.
  • Select and Configure Connectors: Choose from over 100 available connectors, including Azure services, AWS, and on-premises systems. Follow the configuration steps to authenticate and enable data flow.
  • Validate Data Ingestion: Confirm that logs and events are being successfully ingested and are visible in Sentinel’s workspace.
    • Ensure that you validate the data flow from that connector. My preference is to open up the Log Analytics Workspace > Logs > Use some of the below KQL examples to validate your data is flowing as expected:
      AzureActivity | limit 10
      or
      OfficeActivity | limit 10
      or
      CommonSecurityLog | limit 10
    • Use the KQL and replace the table names used above to match the data you are ingesting.

2. Configuring Analytics Rules

Analytics rules define how incidents are detected and generated. In Sentinel > Analytics

  • Access Analytics: Select Analytics from the Sentinel sidebar.
  • Create a New Rule: Choose + Create and select the appropriate rule type (scheduled, anomaly, or fusion).
  • Define Rule Logic: Specify conditions, thresholds, and logic expressions that determine when an alert becomes an incident.
  • Set Incident Settings: Configure how incidents are grouped, what information they contain, and how they’re prioritized.
  • Review and Deploy: Validate the configuration and enable the rule.

The following KQL can be used to create an analytics rule in Sentinel when you need to be alerted for a user creating an Exchange forwarding rule to a destination outside your tenant:

OfficeActivity
| where RecordType == "ExchangeAdmin"
| where Operation == "New-InboxRule"
| extend RuleActions = parse_json(tostring(RawData))["RuleActions"]
| mv-expand RuleActions
| where tostring(RuleActions.ActionType) == "ForwardTo"
| where tostring(RuleActions.ActionRecipients) contains "external"
| project TimeGenerated, UserId, UserType, ClientIP, Operation, RuleActions

3. Creating Automation Rules

Automation rules dictate how incidents are handled automatically.

  • Open Automation Rules: Navigate to Automation > Automation rules.
  • Add a New Rule: Click + Add and provide a name and description.
  • Define Conditions: Set criteria such as incident severity, status, or specific entities involved.
  • Specify Actions: Choose actions like changing the incident’s status, assigning it to a user, or triggering a playbook.
    • You can use this automation rule to add comments, trigger a playbook, or auto-classify the incident type based on conditions in the incident or alert.
  • Set Execution Order: Arrange the rule order to manage priority and dependencies.
  • Activate the Rule: Save and enable the rule for immediate effect.

4. Designing Playbooks

Playbooks automate complex response actions using Azure Logic Apps. Designing playbooks in Microsoft Sentinel is a crucial step in automating incident response processes. Playbooks leverage Azure Logic Apps to create automated workflows that execute predefined actions when specific conditions are met. This ensures consistent and rapid responses to security incidents.

The process involves defining triggers—events that initiate the playbook, such as the creation of an incident—and specifying actions, like sending notifications, isolating compromised devices, or creating tickets in a ticketing system. By configuring these automated responses, organizations can minimize the time to react to threats, reduce the risk of human error, and ensure standardized handling of incidents.

Testing and validating playbooks in a controlled environment are essential to ensure they function as intended, providing a robust and reliable mechanism for enhancing security operations.

  • Access Playbooks: Under Automation, select Playbooks.
  • Create a Playbook: Click + Create and choose Playbook with Azure Logic Apps.
  • Design the Workflow:
    • Trigger: Define what initiates the playbook (e.g., when an incident is created or updated).
    • Actions: Add steps using a drag-and-drop interface to send notifications, create tickets, or execute remediation scripts.
  • Configure Connectors: Authenticate any external services or applications involved in the workflow.
  • Test the Playbook: Use sample data to ensure it functions as intended.
  • Deploy and Monitor: Save the playbook and monitor its execution during incidents.

Real-World Use Cases

Phishing Attack Mitigation

Scenario: Employees report receiving suspicious emails that could be phishing attempts.

Automated Triage Actions:

  • Detection: Analytics rules identify emails with known phishing signatures or anomalous characteristics.
  • Incident Creation: Sentinel generates an incident flagged with high severity.
  • Automated Response:
    • Playbook Execution: A playbook is triggered to quarantine the emails, block the sender domain, and reset affected users’ credentials.
    • Notification: Security teams receive alerts with detailed incident reports.
    • User Communication: Automated emails educate users about the phishing attempt and reinforce best practices.

Insider Threat Detection

Scenario: Unusual data access patterns suggest a possible insider threat.

Automated Triage Actions:

  • Anomaly Detection: Machine learning models in Sentinel detect deviations from normal user behavior, such as accessing sensitive files outside business hours.
  • Incident Prioritization: Automation rules escalate the incident due to its potential impact.
  • Automated Response:
    • Access Revocation: A playbook disables the user’s access pending investigation.
    • Logging and Preservation: All related activities are logged for forensic analysis.
    • Stakeholder Alert: Key personnel are notified, including HR and legal teams.

Ransomware Attack Response

Scenario: Multiple endpoints exhibit signs of ransomware encryption.

Automated Triage Actions:

  • Alert Correlation: Fusion rules link related alerts across devices to recognize a widespread attack.
  • Immediate Isolation:
    • Network Segmentation: Playbooks disconnect affected devices to prevent lateral movement.
    • Backup Activation: Initiate data backup protocols to secure critical information.
  • Rapid Communication: Send urgent notifications to the security team with action plans and containment strategies.

Best Practices for Effective Automated Triage

To maximize the benefits of automated triage:

  • Regularly Update Detection Logic: Keep analytics rules and threat intelligence feeds current to recognize the latest attack vectors.
  • Fine-Tune Machine Learning Models: Continuously train models with new data to improve detection accuracy and reduce false positives.
  • Thoroughly Test Playbooks: Validate playbooks in a controlled environment to ensure they perform as expected without unintended consequences.
  • Implement Role-Based Access Control (RBAC): Restrict access to critical automation components to prevent unauthorized changes.
  • Monitor and Review Automation Performance:
    • Dashboards and Reports: Use built-in tools to track the effectiveness of automated actions.
    • Feedback Loops: Encourage analysts to provide feedback on automation outcomes for continual improvement.

Conclusion

Automated triage in Microsoft Sentinel is not merely a convenience—it’s an essential component of modern security operations. By leveraging AI, machine learning, and robust automation tools, organizations can:

  • Stay Ahead of Threats: Detect and respond to attacks faster than adversaries can exploit vulnerabilities.
  • Optimize Resources: Free up security teams to focus on strategic initiatives rather than being bogged down by manual tasks.
  • Enhance Security Posture: Build a resilient defense system capable of adapting to the ever-evolving cyber threat landscape.

Embracing automated triage positions your organization at the forefront of cybersecurity excellence, ready to tackle current challenges and future uncertainties.