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NDR vs. EDR: 6 Key Differences and How to Choose


January 28, 2025
Last Updated: January 31, 2025
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What Is Endpoint Detection and Response (EDR)? 

Endpoint detection and response (EDR) is a cybersecurity solution focused on monitoring and responding to threats at the endpoint level—individual devices like laptops, servers, and workstations. It involves continuous monitoring and the collection of activity data from endpoints, enabling security teams to detect potential intrusions and malicious activities in real-time. 

EDR solutions offer forensic tools for threat hunting, allowing security teams to investigate and analyze patterns of zero-day threats and persistent attackers. EDR systems use a combination of automated detection mechanisms and manual analysis. They use machine learning and behavioral analysis to identify anomalies and suspicious activities. 

In addition to alerting security teams, EDR provides context and actionable insights for a swift response. Integrated threat intelligence further improves the ability to correlate data across multiple endpoints.

What Is Network Detection and Response (NDR)? 

Network detection and response (NDR) focuses on the entire network, observing traffic patterns and communications to identify potential security threats. Unlike EDR, which concentrates on individual endpoints, NDR tracks anomalies across the network’s ecosystem. 

It analyzes network traffic using analytics, machine learning, and AI to recognize patterns associated with malicious behaviors, including lateral movement and data exfiltration. NDR solutions continuously scan network data to detect threats that have bypassed traditional perimeter security measures like firewalls and intrusion prevention systems. 

By accumulating network packet data, NDR tools provide detailed visibility into network activities, offering an understanding of what is occurring across different segments. This enables a more coordinated response to cyber threats, as security personnel can see the attack progression and track it back to the source.

This is part of a series of articles about EDR tools

Key Features of EDR

EDR solutions offer a range of capabilities to detect, investigate, and respond to endpoint threats:

  • Real-time threat detection: Continuously monitor endpoint activities, identifying malicious behaviors, unauthorized access attempts, or unusual activity patterns in real time. They use behavioral analytics and machine learning to detect threats that may evade signature-based antivirus software.
  • Automated response capabilities: Can automatically initiate pre-configured responses to contain threats, such as isolating compromised devices, terminating malicious processes, or blocking suspicious connections.
  • Incident investigation and forensic analysis: Provide forensic capabilities, including the ability to trace the timeline of an attack, identify how the breach occurred, and determine the scope of compromise.
  • Threat hunting: Allow security analysts to proactively search for threats by analyzing endpoint data and hunting for indicators of compromise (IoCs) or tactics, techniques, and procedures (TTPs) used by attackers.
  • Integration with threat intelligence: Leverage threat intelligence feeds to provide contextual information about detected threats, such as IP addresses, domains, or file hashes known to be associated with malicious activities.

Key Features of NDR

NDR tools provide insights into network activities, enabling organizations to detect and respond to threats that traditional security measures might miss:

  • Network traffic analysis: Analyze raw network traffic and metadata, monitoring both north-south (external) and east-west (internal) traffic. This ensures visibility into suspicious activities like lateral movement, privilege escalation, and unusual data transfers.
  • Behavioral anomaly detection: Using machine learning models, NDR systems establish a baseline of normal network behavior and detect deviations that may indicate potential threats, such as command-and-control communications or data exfiltration attempts.
  • Encrypted traffic analysis: Can analyze encrypted traffic patterns without decrypting the data, leveraging metadata and flow characteristics to identify threats while preserving privacy and compliance.
  • Threat visualization and correlation: Provide a unified view of detected threats, correlating data across the network to visualize the progression of an attack.
  • Integration with security ecosystems: NDR solutions integrate with other security tools, such as SIEMs, firewalls, and endpoint protection systems, enabling a coordinated defense strategy.

Tips From the Expert

In my experience, here are tips that can help you effectively implement and maximize the value of EDR and NDR solutions:

  1. Align solution choice with your threat model: If the organization faces endpoint-heavy threats like ransomware or insider misuse, prioritize EDR. For threats involving lateral movement, encrypted traffic, or multi-stage attacks, NDR is more effective.
  2. Use behavioral baselines to enhance both EDR and NDR: Train both systems on a baseline of normal endpoint and network activity. This improves anomaly detection and reduces false positives for threats that deviate from typical behavior.
  3. Integrate threat intelligence feeds into both platforms: Enrich detection capabilities by incorporating real-time threat intelligence, enabling EDR and NDR to detect known indicators of compromise (IOCs) and improve contextual threat analysis.
  4. Implement EDR to reduce dwell time for endpoint breaches: Use EDR to identify initial compromise attempts quickly. Complement it with NDR to track and respond to lateral movements, ensuring full threat containment.
  5. Leverage NDR for encrypted traffic monitoring: Many attackers exploit encrypted communications to bypass endpoint detection. Use NDR tools capable of encrypted traffic analysis to flag suspicious patterns without violating privacy.

Eyal Gruner is the Co-Founder and Board Director at Cynet. Previously, he served as the company’s CEO for nine years, guiding its growth from the very beginning. He is also Co-Founder and former CEO of BugSec, Israel’s leading cyber consultancy, and Versafe, acquired by F5 Networks. Gruner began his career at age 15 by hacking into his bank’s ATM to show the weakness of their security and has been recognized in Google’s security Hall of Fame.

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EDR vs. NDR: Key Differences

Here’s an overview of the main differences between these two types of security solutions.

1. Core Functions

EDR’s primary function is to manage endpoint-level threats by monitoring device-specific activities. It relies on data from individual endpoints to detect and respond to suspicious behaviors, making it suitable for forensic investigation and threat hunting. EDR solutions focus on endpoint integrity, supporting post-breach analysis.

NDR focuses on the overarching network, analyzing all communications and traffic flowing across the network. Its function is to detect threats that might spread laterally across the network or exploit multi-step attack methods. NDR is best for environments where understanding network dynamics and stopping in-progress network threats is critical.

2. Response Mechanism

EDR systems provide endpoints with automated capabilities to contain and remediate threats through predefined measures like isolating affected devices or killing processes. This mechanism helps mitigate endpoint-specific threats quickly without affecting the broader network system. 

NDR’s response mechanism involves isolating network segments and redirecting traffic to limit threat propagation. Its focus is on minimizing the spread of threats across the network infrastructure. NDR tools equip security teams with an architectural view of the threat’s trajectory, allowing them to implement network-wide responses that EDR might not address.

3. Data Sources

EDR draws its data primarily from endpoints, leveraging logs, file modifications, and process activity data. This endpoint-centric approach is pivotal for granular analysis and detailed incident responses, yet it may miss network-based threats that fall outside the endpoint perimeter.

NDR pulls data from network traffic capturing, metadata analysis, and flow information. This enables a wider net for threat detection, capturing threats that traverse multiple network vectors. However, it may lack the granularity EDR provides.

4. Detection Methods

EDR detection emphasizes detailed endpoint behavior analysis using signatures, heuristics, and anomaly-based detections. These systems are useful for identifying deviations in endpoint activities but might miss threats hidden at the broader network level.

NDR utilizes traffic analysis, anomaly detection, and pattern recognition to identify threats. Employing AI and machine learning improves its capability to detect complex threats dispersed across network streams. 

5. Cost

EDR solutions generally involve costs associated with software subscriptions, maintenance, and integration with existing IT environments.

NDR systems may come with higher upfront infrastructure costs, owing to the need for hardware and software setups to manage network-wide visibility and threat detection. However, the return on investment can be significant when considering the broad security coverage it offers, especially for large or complex network environments.

6. Use Cases

EDR is well-suited for organizations prioritizing endpoint security, crucial in industries where sensitive data is frequently processed, such as financial and healthcare sectors. Its deep analysis capabilities allow for efficient handling of insider threats and malware at the endpoint level.

NDR is suitable for enterprises focused on securing their entire network infrastructure, particularly those with complex architectures or those facing advanced persistent threats. It is beneficial in environments like large corporate networks, cloud systems, and data centers.

Related content: Read our guide to EDR healthcare

NDR vs. EDR: How to Choose?

When deciding between NDR and EDR, it is essential to evaluate the organization’s security requirements, IT infrastructure, and threat landscape. Here are key considerations to guide your decision:

Organizational Needs and Risk Profile

  • Endpoint-centric security: If your organization relies heavily on endpoints such as workstations, laptops, or mobile devices, EDR may be the better fit. It offers visibility into endpoint activities, making it ideal for detecting malware, insider threats, and file-based attacks.
  • Network-wide protection: Organizations with complex or distributed network environments, such as multi-cloud infrastructures or large data centers, may find NDR indispensable. It provides insights into network traffic, helping detect advanced persistent threats (APTs) and lateral movements.

Visibility Requirements

  • Granular endpoint insights: EDR excels at monitoring and analyzing endpoint-specific activities like process execution, file access, and user behavior. This level of detail is crucial for forensic investigations and compliance reporting.
  • Holistic network view: NDR provides visibility across the entire network, identifying anomalies that might go unnoticed at the endpoint level. This is critical for detecting encrypted threats, command-and-control traffic, and data exfiltration attempts.

Detection and Response Capabilities

  • Targeted response at endpoints: EDR solutions enable rapid responses, such as isolating compromised devices or killing malicious processes.
  • Network-level containment: NDR tools can quarantine suspicious network segments or reroute traffic to limit an attack’s spread.

Hybrid Approach: The Case for XDR

For organizations seeking comprehensive security coverage, extended detection and response (XDR) is an emerging solution that combines the strengths of EDR and NDR. XDR integrates data from endpoints, networks, and other sources into a single platform, offering unified visibility and coordinated response capabilities.

By choosing XDR, organizations can benefit from:

  • Improves threat detection by correlating data across multiple domains.
  • Simpler incident response workflows.
  • Reduced complexity through a consolidated security platform.

Security Automation with Cynet

Cynet is the world’s first Autonomous Breach Protection platform that natively integrates the endpoint, network and user attack prevention & detection of XDR with the automated investigation and remediation capabilities of SOAR, backed by a 24/7 world-class MDR service.  End to end, fully automated breach protection is now within reach of any organization, regardless of security team size and skill level.

XDR Layer: End-to-End Prevention & Detection

  • Endpoint protection—multilayered protection against malware, ransomware, exploits and fileless attacks.
  • Network protection—protecting against scanning attacks, MITM, lateral movement and data exfiltration.
  • User protection—preset behavior rules coupled with dynamic behavior profiling to detect malicious anomalies.
  • Deception—wide array of network, user, file decoys to lure advanced attackers into revealing their hidden presence.

 SOAR Layer: Response Automation

  • Investigation—automated root cause and impact analysis.
  • Findings—actionable conclusions on the attack’s origin and its affected entities.
  • Remediation—elimination of malicious presence, activity and infrastructure across user, network and endpoint attacks.
  • Visualization—intuitive flow layout of the attack and the automated response flow.

MDR Layer: Expert Monitoring and Oversight

  • Alert monitoring—First line of defense against incoming alerts, prioritizing and notifying customers on critical events.
  • Attack investigation—Detailed analysis reports on the attacks that targeted the customer.
  • Proactive threat hunting—Search for malicious artifacts and IoC within the customer’s environment.
  • Incident response guidance—Remote assistance in isolation and removal of malicious infrastructure, presence and activity.

Simple Deployment

Cynet can be deployed across thousands of endpoints in less than two hours. It can be immediately used to uncover advanced threats and then perform automatic or manual remediation, disrupt malicious activity and minimize damage caused by attacks.

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