From endpoint to XDR: Operationalize Microsoft Defender for Endpoint data in Elastic Security

Many security teams often find it difficult to detect and respond to threats because of fragmented visibility and isolated endpoint data. This challenge led to the development of extended detection and response (XDR), which integrates endpoint insights with contextualized data from networks, cloud environments, and identity systems. Endpoint security tools are essential for visibility into endpoint threats, but they only provide a limited view. Endpoint data alone lacks the broader context needed to fully understand and mitigate threats across an organization’s entire attack surface.

True XDR requires a comprehensive approach that goes beyond isolated endpoint telemetry. Elastic Security solves this challenge with AI-driven security analytics, delivering unified threat detection, investigation, and response without the need for yet another XDR tool. Elastic provides a single platform that eliminates silos, reduces tool sprawl, and cuts unnecessary costs — providing a more efficient and holistic defense against modern cyber threats.

Elastic Security integrates with Microsoft Defender for Endpoint (MDE) and operationalizes MDE data alongside signals from network, identity, and cloud sources, offering a complete threat picture. By ingesting MDE telemetry, whether directly or via Microsoft 365 Defender (Microsoft Defender XDR), into Elastic Security, organizations can gain deeper visibility and take decisive security actions with advanced analytics, AI-driven assistance, and robust response capabilities. Backed by Elastic Security Labs’ threat research and machine learning, Elastic’s open security ecosystem ensures that defenders can correlate MDE alerts with other data sources, accelerating investigations and enabling proactive threat mitigation.

The broader Microsoft 365 Defender (XDR) integration enables ingestion from multiple Defender XDR products, including Microsoft Defender for Endpoint, Microsoft Defender for Office 365, Defender for Identity, and Defender for Cloud Apps, among others. To differentiate MDE-specific data within Elastic Security, teams should use the event.provider ECS field (event.provider:“MicrosoftDefenderForEndpoint”) as another filter on top of m365_defender event.module ECS field. This filtering capability allows analysts to isolate endpoint-related events while still leveraging the full breadth of XDR telemetry.

By unifying MDE telemetry with other security domains, Elastic Security provides centralized visibility, ensuring that endpoint alerts are analyzed within the broader attack surface. SOC teams can instantly correlate MDE alerts with network traffic, cloud activity, and identity-based signals, enabling faster detection of sophisticated threats.

Elastic Security brings powerful detection and response capabilities to Microsoft Defender for Endpoint data. By ingesting MDE telemetry, security teams can immediately leverage Elastic’s extensive library of prebuilt detection rules, behavioral analytics, and machine learning models — without needing to build custom analytics from scratch.

Elastic’s machine learning models detect anomalies in MDE data, identifying suspicious behaviors that traditional rule-based detections might miss. Analysts can also define custom rules to tailor detections to their organization’s unique threat landscape. Because Elastic’s detection engine operates on an open, extensible data model, organizations benefit from unified detections spanning endpoints, cloud workloads, identity systems, and network data.

With MDE data centralized in Elastic, security teams benefit from a rich set of investigation tools that enhance threat hunting and response workflows.

Custom knowledge source integration
Elastic Security 8.16's AI Assistant now integrates with custom knowledge sources, including threat intelligence feeds, internal playbooks, and wikis, to deliver answers tailored to an organization's specific security practices and threat landscape. Analysts can leverage their environment's unique procedures and past incidents when investigating alerts. For example, an analyst could ask, "Have we identified the presence of this malware file in our environment before?" and the AI Assistant would search indexed internal incident reports or threat intel feeds in Elastic for relevant information.

MDE data becomes instantly actionable through Kibana dashboards, offering real-time insights into endpoint alerts, attack patterns, and security trends. Analysts can trace process activity using the Analyzer, reconstruct incidents with Timelines, and visualize threat actor behaviors mapped to MITRE ATT&CK.

Correlate MDE telemetry with Timelines
Timelines allow analysts to reconstruct security incidents by correlating MDE alerts with other data sources. For example, if MDE detects a malicious executable, analysts can use Timelines to correlate this event with suspicious login activity from the same host, uncovering potential attacker behavior.

Elastic Security now supports bidirectional response actions for MDE, allowing analysts to isolate and release an endpoint in order to contain threats directly from the Elastic interface without switching between tools. By integrating these response actions, security teams can dramatically reduce mean time to respond (MTTR) and limit attacker dwell time.

The more high-fidelity data organizations bring into Elastic Security, the stronger their security posture becomes. While Microsoft Defender for Endpoint provides deep endpoint visibility, it is crucial to consider long-term data retention and analytics capabilities. Elastic Security offers cost-effective long-term data retention, scalable storage options that enable security teams to maintain access to historical data for compliance, forensic investigations, and advanced threat-hunting use cases.

Organizations can use searchable snapshots to retain Microsoft Defender for Endpoint telemetry without the need for frequent rehydration. This allows analysts to perform historical threat-hunting and forensic analysis on years' worth of security data with minimal storage costs. Additionally, Elastic’s cross-cluster search capabilities allow teams to correlate Defender for Endpoint telemetry across multiple Elastic deployments, ensuring a unified security view across different environments.

Beyond storage, Elastic’s Search AI Lake enables advanced analytics and machine learning on Defender for Endpoint data. Security teams can apply behavioral analytics, anomaly detection, and custom machine learning models to uncover sophisticated threats that traditional detection rules may miss. Elastic’s open, extensible ecosystem ensures that Defender for Endpoint telemetry is not just stored, but actively leveraged to strengthen security operations over time. 

By centralizing Microsoft Defender for Endpoint data in Elastic Security, organizations gain a robust security data lake that provides deep visibility, powerful analytics, and strategic long-term security insights.