In today’s increasingly complex and hostile cyber threat landscape, the need for visibility, speed, and intelligence across enterprise networks has never been greater. Security Information and Event Management (SIEM) systems have long served as the central nervous system of many organizations’ security operations centers (SOCs), collecting, normalizing, and analyzing logs from across the digital estate. But as attackers become stealthier and more advanced, the limitations of log-based detection alone have become apparent.
This is where Network Detection and Response (NDR) enters the picture—offering complementary, high-fidelity insights by monitoring network traffic in real-time. When integrated effectively, NDR can supercharge SIEM platforms, enriching alerts, enabling faster threat detection, and ultimately improving security outcomes.
In this blog post, we’ll dive deep into the role of NDR in SIEM, how these tools complement each other, and why a combined approach is essential for modern cybersecurity defense.
What is SIEM?
Security Information and Event Management (SIEM) platforms are centralized systems that collect and analyze log data from across an organization’s infrastructure—servers, endpoints, firewalls, identity providers, cloud services, and more. They are designed to:
Aggregate and correlate data from disparate sources
Generate alerts based on defined rules or analytics
Support investigations with timeline views and data querying
Assist with compliance reporting (e.g., PCI-DSS, HIPAA, GDPR)
While SIEMs provide a comprehensive overview of security events and trends, they are heavily dependent on the quality and completeness of logs. This poses challenges when attackers use techniques that do not generate traditional logs or tamper with log sources.
What is NDR?
Network Detection and Response (NDR) focuses on real-time monitoring and analysis of network traffic to detect threats and suspicious behavior. NDR platforms use machine learning, behavioral analytics, threat intelligence, and signature-based techniques to spot anomalies that indicate potential attacks such as:
Lateral movement
Command and control (C2) activity
Data exfiltration
Unusual east-west traffic
DNS tunneling
Encryption misuse
Unlike SIEM, which relies on logs, NDR inspects raw packet data or flow data, offering a unique perspective that is harder for attackers to evade.
Why SIEM Alone Isn’t Enough
Despite the power of SIEM platforms, they are not infallible. Some of the most critical challenges SIEMs face include:
1. Incomplete Data Coverage
Not all network activities generate logs. For example, attackers may use protocols or stealthy techniques that bypass endpoint logging mechanisms.
2. Log Tampering and Blind Spots
Advanced attackers can disable or modify logging to hide their activities. Cloud environments also add complexity, where logging may be misconfigured or insufficient.
3. Alert Fatigue
SIEMs are notorious for generating a high volume of alerts, many of which are false positives. SOC teams can become overwhelmed and miss real threats.
4. Latency in Detection
Traditional log ingestion and rule-based detection methods may introduce delays, reducing the window for incident response.
NDR addresses these weaknesses by providing a tamper-resistant, real-time view of network behavior, ensuring better detection and faster response.
The Power of SIEM + NDR
When integrated properly, SIEM and NDR provide a 360-degree view of the threat landscape—bringing together log data and network telemetry for more robust detection and response. Here’s how they work together:
1. Enriched Alerts
NDR can feed high-fidelity alerts into the SIEM, complete with context such as the source/destination IPs, associated users, protocols used, and session metadata. This allows SIEMs to make better correlations and reduce false positives.
2. Behavioral Analytics and Threat Hunting
While SIEMs often use predefined rules, NDRs apply unsupervised learning models that detect unknown or emerging threats. By bringing this behavioral data into SIEMs, threat hunters can investigate deeper and identify stealthy activity faster.
3. Accelerated Incident Response
NDR tools often include automated response capabilities—such as quarantining suspicious hosts or blocking traffic. When integrated into SIEM workflows, this can lead to faster containment of threats.
4. Richer Investigation Context
During an incident, correlating log data with NDR metadata helps analysts build a more complete picture. For example, SIEM might show a failed login attempt, while NDR reveals that it was followed by lateral movement or data exfiltration.
5. Compliance and Reporting
NDR can add valuable forensic and historical data to support compliance needs. SIEMs can include NDR telemetry in audit trails and reports, enhancing regulatory adherence.
Use Case Examples
1. Insider Threat Detection
An employee begins accessing sensitive systems they normally don’t interact with. The SIEM logs unusual access attempts, while NDR flags anomalous traffic patterns—such as large data transfers to external domains.
2. Ransomware Containment
A SIEM might detect a suspicious executable being downloaded, but an NDR system will observe C2 communications and lateral spread across the network. Together, they can identify and isolate affected systems more quickly.
3. Zero-Day Attack
A SIEM with static rules may not catch a zero-day exploit, but an NDR system could detect unusual protocol use or encryption anomalies—alerting analysts before damage is done.
Best Practices for Integrating NDR with SIEM
To get the most value out of this powerful pairing, organizations should follow key best practices:
1. Centralize Data Ingestion
Ensure that the SIEM is ingesting telemetry from the NDR platform in a normalized, structured format. Use APIs or syslog for efficient integration.
2. Create Correlation Rules
Develop rules that correlate NDR alerts with log events in the SIEM. For instance, link suspicious DNS traffic flagged by NDR with authentication failures in logs.
3. Use a Common Data Model
Adopt or map data into a common schema (like the Elastic Common Schema or MITRE ATT&CK framework) for seamless analysis and dashboarding.
4. Automate Response Workflows
Use SOAR (Security Orchestration, Automation, and Response) playbooks to act on combined SIEM+NDR intelligence—such as isolating devices or notifying analysts.
5. Continuous Tuning
Regularly refine detection logic, anomaly baselines, and data retention policies. Both NDR and SIEM outputs should inform each other to reduce noise and increase precision.
NDR and the Future of Threat Detection
With the rise of encrypted traffic, cloud-native infrastructure, and remote workforces, network boundaries have blurred—but network behavior remains a goldmine of intelligence. NDR platforms are evolving to provide visibility into east-west traffic, encrypted communications, and cloud workloads—areas where traditional tools falter.
Meanwhile, SIEM platforms are becoming more analytics-driven, incorporating UEBA (User and Entity Behavior Analytics), threat intelligence feeds, and machine learning. Together, SIEM and NDR form the backbone of proactive detection and response strategies.
Organizations that harness both can transition from reactive firefighting to proactive threat hunting—detecting adversaries before they do damage.
Conclusion
Security teams can no longer rely solely on logs to detect modern threats. Network Detection and Response (NDR) brings critical visibility and context to the table, filling gaps left by SIEM systems. When combined, SIEM and NDR offer unparalleled insights, detection speed, and investigative power—enabling SOCs to respond to threats with agility and confidence.
As cyber threats continue to evolve, the integration of NDR into the SIEM ecosystem is not just a nice-to-have—it’s a must for organizations aiming to stay ahead of adversaries in the digital arms race.