CrowdStrike + Microsoft: The Agentic SIEM Integration That Just Made Your Defender Investment 5X Faster and 50% Cheaper + Video

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Introduction:

The convergence of endpoint detection and response (EDR) and security information and event management (SIEM) has long been a goal for security operations centers (SOCs) seeking to eliminate data silos. CrowdStrike’s Falcon Next-Gen SIEM now ingests Microsoft Defender for Endpoint telemetry natively, enabling unified detection without the need for additional deployments or migration friction, effectively translating legacy SIEM queries into CrowdStrike Query Language (CQL) and delivering a 5X faster streaming rate with 50% lower storage costs.

Learning Objectives:

  • Understand how to integrate Microsoft Defender for Endpoint telemetry into CrowdStrike Falcon Next-Gen SIEM without deploying new agents.
  • Learn to translate legacy SIEM queries (e.g., Splunk SPL, QRadar AQL) into CrowdStrike Query Language (CQL) for unified hunting.
  • Implement operational workflows that bridge SOC detection with ITSM and NOC processes for faster incident resolution.

You Should Know:

  1. Native Integration: Ingesting Microsoft Defender Telemetry Without Additional Agents

The core innovation is the native ingestion pipeline that pulls Microsoft Defender for Endpoint (MDE) data directly into the Falcon platform. This is not a log forwarder or a third-party connector; it is a cloud-native integration that leverages APIs to stream telemetry. From a deployment perspective, organizations running Defender can enable this integration via the Falcon console without touching endpoints.

Step‑by‑step guide to verify and configure the integration:

  1. Prerequisites: Ensure you have administrative access to both the CrowdStrike Falcon console and the Microsoft 365 Defender portal. You need a CrowdStrike subscription with Falcon Next-Gen SIEM enabled and Microsoft Defender for Endpoint (Plan 1 or 2) active.
  2. API Registration: In Microsoft Azure, register an application to grant CrowdStrike permissions. Navigate to Azure AD > App registrations > New registration. Name it “CrowdStrike SIEM Integration.”
  3. API Permissions: Assign the following Microsoft Graph API permissions: `AdvancedHunting.Read.All` and Alert.Read.All. Grant admin consent for your organization.
  4. Retrieve Credentials: Note the Tenant ID, Client ID, and generate a `Client Secret` for the registered app.
  5. Configure Data Connector in Falcon: Log into the CrowdStrike Falcon console. Navigate to Data Connectors > Add New. Select Microsoft Defender for Endpoint. Input the Tenant ID, Client ID, and Client Secret.
  6. Test the Connection: CrowdStrike will verify the credentials and begin ingesting telemetry. You should see Defender alerts and advanced hunting tables appear in the Falcon data lake within minutes.

  7. Query Translation: Converting Legacy SIEM Logic to CrowdStrike Query Language (CQL)

For SOC teams migrating from legacy SIEMs, the ability to automatically translate queries is critical. The platform supports automated translation, but analysts must understand CQL syntax to refine hunts.

Example: A common Splunk query to find PowerShell execution:

index=windows sourcetype="WinEventLog:PowerShell" ScriptBlockText="Invoke-"

Translated to CQL for Falcon:

event_simpleName = ProcessRollup2 
| where FileName =~ "powershell.exe" 
| where CommandLine contains "Invoke-"
| table ContextTimeStamp, ComputerName, UserName, CommandLine

Step‑by‑step guide for manual translation:

  1. Identify Data Sources: In Falcon, use `event_simpleName` to filter event types. For Defender telemetry, you might use `DeviceProcessEvents` or DeviceNetworkEvents.
  2. Field Mapping: Legacy SIEMs often use fields like sourcetype. In CQL, you use `event_simpleName` or platform-specific tables. Use the `| schema` command to view available fields for a specific dataset.
  3. Filtering: Use `| where` for conditionals. Note that CQL is case-insensitive but best practices suggest using `=~` for case-insensitive string matching.
  4. Aggregation: Use `| groupBy` for aggregation, similar to Splunk’s | stats.

– Splunk: `| stats count by user`
– CQL: `| groupBy(

, function=count())`
5. Testing: Use the Investigate tab in Falcon to run queries against historical data before operationalizing them as scheduled searches or alerts.

<ol>
<li>Performance Optimization: Leveraging 5X Faster Streaming for Threat Hunting</li>
</ol>

The claim of “5X faster streaming” is not just a marketing point; it represents the architectural shift from batch processing to real-time streaming analytics. Traditional SIEMs often introduce latency (10–30 minutes) between log ingestion and searchability. Falcon’s architecture makes data available for query within seconds.

<h2 style="color: yellow;">To operationalize this for threat hunting:</h2>

<h2 style="color: yellow;">Step‑by‑step guide to perform real-time hunting:</h2>

<ol>
<li>Access Falcon Console: Navigate to Investigate > SIEM.</li>
<li>Select Time Window: Choose “Live” or “Last 5 minutes” to leverage the streaming capability.</li>
<li>Construct a CQL Query: To hunt for lateral movement using Defender telemetry correlated with Falcon identity data:
[bash]
// Correlate Defender network connections with Falcon process data
DeviceNetworkEvents
| where RemoteIP != LocalIP
| join kind=inner (
ProcessRollup2
| where FileName =~ "wmic.exe"
) on DeviceId
| table Timestamp, DeviceName, RemoteIP, InitiatingProcessCommandLine
  • Use Saved Queries: Save this query as a Scheduled Search to run every minute, effectively creating a detection rule that fires in near real-time.

  • Bridging SOC and ITSM: Operationalizing Alerts for NOC Workflows

    • As noted in the comments, detection is only half the battle. Integrating security events into IT Service Management (ITSM) workflows ensures faster resolution. Falcon Next-Gen SIEM supports webhooks and API integrations to push alerts to platforms like ServiceNow, Jira, or even custom scripts.

    Step‑by‑step guide to integrate with a ticketing system:

    1. Create a Detection Workflow: In Falcon, go to Workflows (or Automation). Create a new workflow triggered by a specific alert severity (e.g., “Critical” or “High”).
    2. Add Action: Select Send Webhook. Configure the endpoint to your ITSM platform’s API.
    3. Craft the Payload: Use a template to include essential data: 
      {
"title": "Falcon Alert: {{alert.name}}",
"description": "Host: {{host.hostname}} | User: {{user.name}} | Command: {{process.command_line}}",
"severity": "{{alert.severity}}",
"source": "CrowdStrike SIEM"
}
    4. Test the Automation: Generate a test alert (e.g., using the Atomic Red Team project) to verify that a ticket is automatically created in the ITSM system.

    5. Linux Command-Line Analysis: Validating Telemetry from Linux Endpoints

    For organizations managing cross-platform environments, both CrowdStrike Falcon and Microsoft Defender for Endpoint support Linux hosts. Security analysts can validate the telemetry integrity from the command line.

    To verify that Defender is sending data to the cloud on a Linux endpoint:

     Check the status of the Defender for Endpoint service
sudo mdatp health

Review the last 50 log entries for connectivity issues
sudo grep "Cloud" /var/log/microsoft/mdatp/microsoft_defender.log | tail -n 50

    To simulate a detection event for testing SIEM ingestion:

     Simulate a suspicious process (e.g., mimicking a reverse shell)
nohup nc -lvnp 4444 &
ps aux | grep nc
 Use Falcon's RTR (Real Time Response) to verify the event appears in the console

    In Falcon, you can use RTR to query the endpoint directly:

     From Falcon RTR shell
runscript -Raw=“ps aux | grep nc”
    1. Cost Optimization: Analyzing Storage and Retention with the 50% Reduction

    The 50% lower storage costs are achieved through data deduplication, compression, and tiered storage. Traditional SIEMs charge by ingest volume (GB/day). Falcon charges based on workload (endpoints) rather than log volume, incentivizing data ingestion.

    To audit your cost savings:

    1. Estimate Current Ingest: In your legacy SIEM, export a report of daily ingest volume for Defender logs (e.g., Windows Event Forwarding logs).
    2. Check Falcon Ingestion: In the Falcon console, navigate to Usage > Data Ingestion. Compare the volume of data stored from Defender sources.
    3. Retention Policy: Configure retention policies in Falcon to optimize further. Navigate to Settings > Data Retention. Set longer retention for compliance-critical data (e.g., 12 months) and shorter for high-volume, low-value logs (e.g., 30 days).

    What Undercode Say:

    • Key Takeaway 1: The CrowdStrike-Microsoft integration removes the traditional barrier between EDR and SIEM, allowing organizations to keep their Defender investment while adopting a modern, agentic SIEM architecture.
    • Key Takeaway 2: Operationalizing security requires more than just detection; bridging SOC data with ITSM workflows via APIs and webhooks is essential for reducing mean time to resolution (MTTR).

    The shift from “rip and replace” to “integrate and enhance” marks a maturation of the cybersecurity market. By allowing Falcon to ingest Defender telemetry natively, CrowdStrike acknowledges the reality of heterogeneous environments while pushing the SOC toward a unified data lake. For analysts, this means less time managing connectors and more time hunting. The use of CQL over traditional SIEM query languages also suggests a standardization on SQL-like syntax, lowering the barrier to entry for new analysts. However, organizations must carefully audit their API permissions to ensure the principle of least privilege is maintained—excessive permissions to the Microsoft Graph API could inadvertently expose broader telemetry than intended. The future of SIEM lies in this composable model where best-of-breed tools can coexist without friction.

    Prediction:

    This integration signals a broader industry trend toward platform consolidation where SIEM becomes a feature of the XDR platform rather than a separate silo. We predict that within 18 months, standalone SIEM vendors will either pivot to a similar ingestion model or face acquisition pressure. The focus will shift from “how much data can you store” to “how fast can you correlate and act,” with AI-driven automation (the “agentic era”) becoming the primary differentiator in SOC efficiency.

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