What is Network Detection and Response (NDR)?

Network Detection and Response (NDR) is a security solution that monitors network traffic to detect suspicious or malicious activity that other tools might miss.

Instead of relying on known threat signatures, NDR uses advanced techniques, such as machine learning and behavioral analytics, to identify unusual patterns in network behavior.

How do Network Detection and Response Work?

Network detection and response work by constantly analyzing the traffic flowing through your network, down to the raw packets and metadata. It pays close attention to every digital conversation between users inside the network or reaching out to the outside world.

But NDR monitors and learns by using behavioral analytics and machine learning. It builds a baseline of what “normal” looks like in your environment. Once that’s in place, any unusual behavior like strange traffic spikes or connections to suspicious IPs triggers an alert.

Here’s what’s happening behind the scenes:

  • Detects abnormal traffic using advanced analytics and known signatures
  • Builds models of normal behavior so it can spot subtle threats quickly
  • Generates real-time alerts to help teams act fast and contain issues early
  • Connects suspicious activity to specific IP addresses or devices for better context
  • Supports forensic investigations by logging detailed evidence for every incident

Importance of Network Detection and Response Platform

Network detection and response are essential because in modern cybersecurity strategy, the quicker you can spot a threat, the faster you can act. An NDR platform constantly monitors your entire network, looking for suspicious behavior so your team can respond immediately.

Here’s how NDR significantly improves your security posture:

Catches Threats Other Tools Might Miss

Traditional security tools typically depend on known signatures or alerts. But modern threats don’t always match known patterns. NDR uses innovative techniques like behavioral analytics and machine learning to spot unusual network traffic even when a threat is new or subtle.

Knows What’s Normal (and What Isn’t)

Your network has its baseline and its own “normal” patterns. NDR platforms continually learn these expected behaviors, instantly noticing if something unusual happens, such as an unexpected login attempt, data leaving your network, or strange connections between devices. Your security team receives an immediate alert, enabling them to respond faster.

Sees Everything Happening on Your Network

Attackers often move quietly, shifting between different systems and devices within your network before causing noticeable harm. An NDR solution tracks all network activities, whether entering, exiting, or traveling internally, providing your security team a clear view of what’s happening. This makes it easier to spot and stop threats before they escalate.

Real-Time Insight

When it comes to security, time is critical. NDR tools analyze your network traffic in real-time, immediately alerting your team when something suspicious occurs. Your team can respond quickly with instant notifications and precise details, reducing risk and limiting potential damage.

Network Detection and Response Use Cases

Network traffic analysis is a crucial factor in cloud and on-premise cybersecurity. Organizations that give up on network detection and response will find they lack the necessary tools for rapid and scalable threat monitoring.

Network detection and response products can significantly contribute to information security maintenance at various points. We describe some of the most important below.

1. Defending Every Connected Asset

Every server, endpoint, application, and IoT device connected to your network is a potential entry point for attackers. NDR continuously monitors these digital touch-points, looking for subtle signs of compromise such as data exfiltration, lateral movement, or communication with known malicious domains.

Why it matters:
You can’t protect what you can’t see. NDR ensures no asset goes unwatched. It reduces blind spots and enables faster containment of threats before they escalate into full-blown incidents.

2. Detecting Lateral Movement

Attackers rarely hit their target immediately after breaching a perimeter (via phishing, compromised VPN, or misconfigured device). They pivot laterally by scanning internal hosts, escalating privileges, and blending in with regular traffic.

NDR tools analyze internal east-west traffic patterns, looking for unusual connections (e.g., user workstations accessing database servers or abnormal RDP sessions between unrelated endpoints). Behavioral baselining flags traffic that deviates from historical norms.

Why it matters:
Lateral movement is a key stage in multi-stage attacks and ransomware campaigns. Stopping it early prevents attackers from gaining a foothold in your most sensitive systems.

2. Insider Threats

Not all threats are external. Rogue employees, negligent insiders, or third-party vendors with access can abuse systems without raising red flags in perimeter tools.

NDR detects unusual user behavior, like accessing large files outside regular working hours, transferring data to unauthorized IPs, or connecting to network parts irrelevant to their role.

Why it matters:
Insiders often operate with legitimate credentials, making traditional rule-based monitoring ineffective. NDR focuses on how someone behaves.

3. Identifying Command-and-Control (C2) Traffic

After malware infects a system, it often “calls home” to a remote server to receive instructions or exfiltrate data. These are known as C2 communications.

NDR detects suspicious beaconing behavior, even in encrypted traffic, when it profiles outbound network activity, predominantly low-frequency, repetitive connections to unknown or untrusted IPs. It doesn’t rely on threat signatures but on traffic characteristics.

4. Monitoring Encrypted Traffic Without Decryption

Over 90% of internet traffic today is encrypted. While this is great for privacy, it also hides malicious activity from many legacy tools.

Rather than decrypting traffic (which raises performance and privacy concerns), NDR evaluates metadata like packet size, frequency, and destination patterns. This will detect anomalies, such as exfiltration hidden in TLS traffic.

Why it matters:

NDR provides deep visibility without compromising encryption, making it ideal for regulated environments where decryption isn’t an option.

5. Retrospective Threat Hunting

Often, threats are discovered after they’ve entered your environment. New indicators of compromise (IOCs) are released weeks after initial exposure.

NDR retains full-fidelity traffic logs or enriched metadata. This allows analysts to search historical network activity using fresh intelligence and track past connections to newly flagged IPs or domains.

Why it matters:
This “time machine” capability helps uncover threats, identify affected systems, and respond before dormant malware activates or data loss escalates.

6. Early Ransomware Detection

Ransomware isn’t dropped immediately; it often follows days of silent reconnaissance, credential harvesting, and movement between systems.

NDR can spot early signals: internal scanning, brute-force attempts on SMB/RDP, spikes in file transfers, or malware staging activity.

Why it matters:
Stopping ransomware before encryption starts is the holy grail of ransomware defense. NDR gives SOC teams the early window to contain and neutralize the threat.

How to Choose a Network Detection and Response Solution?

Here’s a simple checklist of questions and requirements you need to consider before choosing an NDR solution:

Requirements Yes/No
Does the solution combine raw network data with contextual information (asset details, user identities, geolocation)?
Can it automatically map suspicious traffic to specific hosts, applications, or users?
Does it leverage machine learning and behavioral analytics to identify anomalies (vs. relying solely on signatures)?
Can it detect zero-day threats, lateral movement, and encrypted-traffic anomalies?
Are alerts delivered in real time with built-in severity scoring?
Can you customize alert thresholds to reduce noise and focus on critical incidents?
Does it automatically integrate with firewalls, EDR/XDR, or SOAR platforms to isolate or block threats?
Are response playbooks configurable to match your organization’s workflows?
Is the solution available for on-premises, cloud, and hybrid environments?
How lightweight are the sensors or collectors, and can they operate without impacting network performance?
Can it handle your current network and scale as traffic grows?
Does it offer high availability or clustering for mission-critical operations?
Does it consume external feeds (IoCs, TTPs) and enrich detections with global threat data?
Is there support for custom threat intel sources or internal feeds?
Does it provide searchable historical logs and packet capture for retroactive investigations?
Are compliance-ready reports available for regulations like GDPR, HIPAA, or PCI-DSS?
Is there a unified dashboard where SOC analysts can view alerts, timelines, and network maps?
How intuitive is policy configuration, rule tuning, and user-role management?
What SLAs and support options are offered (24/7, regional coverage)?
How frequently are detection rules, ML models, and threat feeds updated?

Benefits of NDR for Modern Cybersecurity

Here are some of the benefits of NDR for modern cybersecurity:

1. Advanced Threat Detection

Attackers are smart. They constantly tweak their strategies to sneak past traditional security methods. NDR uses network behavioral analytics and machine learning to recognize subtle clues that something isn’t quite right. This could be something like unusual login patterns or strange data transfers, even when threats haven’t been seen before.

2. Passive Monitoring with Active Results

Nobody likes security measures that slow down day-to-day operations. The good news is that NDR doesn’t interrupt your network at all. It quietly watches a copy of your traffic, leaving your actual data flow untouched.

For example, because the solution passively monitors traffic from a packet broker or SPAN port, NDR can be deployed quickly without downtime or service disruptions.

3. Comprehensive Anomaly Detection

Sometimes, the most significant threats come from within, whether from employees making honest mistakes or insiders intentionally causing harm. NDR continuously learns what “normal” network behavior looks like.

So, your security team gets an instant alert when something unusual happens, like someone accessing sensitive files at odd hours.

4. Broad Attack Visibility

Attackers rarely complete their objectives with a single action. Instead, they usually leave behind multiple small clues, like tiny digital footprints across the network. NDR catches these clues early, allowing your security team to track every step attackers take.

For example, unlike endpoint solutions, NDR sees every action the attacker takes at the network layer.

5. Accurate Analytics

Many security tools rely heavily on logs, which can be incomplete or unreliable. NDR looks directly at network packets (the actual data traveling through your network), offering more precise, accurate insights without sorting through confusing logs.

6. Out-of-the-Box Detection 

Traditional security tools often require significant upfront configuration, manual tuning, and ongoing maintenance. In contrast, well-designed NDR solutions provide immediate value upon deployment.

They use built-in, optimized algorithms that automatically adapt to the specific characteristics of your network environment, drastically reducing operational overhead.

NDR vs. Other Detection Tools (SIEM, EDR, XDR)

 

Feature SIEM EDR NDR
Data Sources Log files, events from the network, endpoints, and applications Endpoint-level events (host telemetry, logs) Raw network packets, flow data, metadata
Primary Focus Compliance, event correlation, and log management Endpoint threats, malware containment Insider threats, lateral movement, and anomalous network behaviors
Threat Detection Approach Primarily rule/signature-based detection, correlation rules Behavioral analytics, signature & heuristic-based Machine learning, behavioral analysis on network traffic
Real-Time Visibility Medium (limited by log latency) High (real-time endpoint telemetry) High (real-time network analysis)
Anomaly Detection Limited (mostly predefined rules) Strong on endpoints Strong, specifically network-focused
Attack Stage Detection Detection is mostly post-compromise or compliance-oriented Early detection of malware execution, host-level compromise Early-stage and lateral movements, including insider threats and zero-day attacks
Encrypted Traffic Visibility Limited (logs rarely capture encrypted traffic insights) Limited (only at the endpoint level) High (metadata analysis detects threats even within encrypted traffic)
Response Capabilities Typically, manual or via integrated SOAR tools Strong at endpoint isolation/quarantine Automated via integrations (firewalls, SOAR, EDR)
Scalability & Performance Dependent on log ingestion capacity (high overhead at scale) Endpoint agent management overhead Highly scalable with passive network sensors (minimal overhead)
Forensic & Investigation Good (historical log analysis, reporting) Strong (detailed endpoint forensics, process monitoring) Strong (detailed packet capture, historical network events analysis)
Deployment Complexity High (extensive setup, ongoing tuning required) Moderate (agent deployment and policy management) Moderate-to-Low (passive sensors, minimal tuning)
Alert Noise & False Positives High (without careful tuning) Medium-to-high (depends on policies and tuning) Medium-to-low (due to detailed contextual awareness and behavior baselining)

 

Recommendation:
Choose NDR if network visibility and detection of hidden threats like lateral movements and insiders are your priority.

Does Group-IB offer Network Detection and Response?

Network detection and response come as part of the Managed Extended Detection and Response solution. Network traffic analysis is conducted by network sensors integrated with the Malware Detonation Platform, XDR console, and Threat Intelligence. Inside the XDR console, all the components can be easily managed.

In case of an emergency in the network, the response process takes four underlying steps:

  • Network telemetry passes through the data lake.
  • The XDR console acts as a tool to control and monitor deployed network sensors.
  • Extracted objects are sent to the Malware Detonation Platform.
  • Detection is enriched by Threat Intelligence data.

After all these actions, customers get a full-fledged threat analysis with data suitable for developing an asset protection strategy and conducting a forensic investigation.

Interested? Get on a call with us to know more.