Gartner NDR: Insights, Key Findings & The Future Ahead (2025)
- Key Takeaways:
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How does Gartner define NDR?
NDR uses internal sensors and behavior models to detect real-time anomalies in east-west and north-south network flows. -
What gap does NDR fill in security?
It provides visibility into internal traffic that firewalls and SIEMs often miss, closing critical detection blind spots. -
What market trends does Gartner note?
NDR is rapidly growing (≈23% YoY), with increasing adoption and expanding capabilities among mainstream vendors. -
What does this mean for security teams?
NDR is becoming essential for layered defense, especially in complex, high-traffic, cloud and hybrid environments.
Gartner’s NDR Market Guide is a cornerstone for exploring the intricate features and future of the growing Network Detection and Response (NDR) market. As a relatively new part of the cybersecurity toolkit, security teams are rapidly developing their own awareness of the tool: presenting a clear overview, this guide disseminates Gartner’s market research and client interviews into an accessible format.
Since the 2022 Market Report, Gartner’s annual NDR publications have reflected the rapid changes within the field: from 2022’s 19 representative vendors to the several dozen of 2024’s, even major cybersecurity vendors such as Cisco have begun offering NDR capabilities. NDR features have grown substantially, and Gartner’s 2024 report provides the most comprehensive definition so far.
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How Does Gartner Define NDR?
NDR deploys within an organization’s internal networks: its sensors then ingest raw packet data alongside any associated metadata, and assemble it into a granular model of each network’s day-to-day behaviors. This behavioral model allows for the immediate detection of abnormal activity across both internal (east-west) and external (north-south) network traffic. Delivered via a mix of hardware and software-based sensors, NDR deployments are managed through orchestration consoles, while their alerts can be fed into pre-existing workflow dashboards, and – as of 2024 – automated playbooks.
To better define what NDR is, Gartner includes the components that exclude a product from NDR lists. Some of these excluding features include tools that depend on a prerequisite platform—such as requiring a SIEM or firewall for operation; this doesn’t meet the standalone criteria that’s central to NDR. Similarly, platforms that prioritize network forensics through extensive PCAP storage and retrospective analysis – rather than real-time detection – fall short of NDR’s real-time threat identification demands. Finally, specialized solutions that are built exclusively for cyber-physical systems or log analysis also diverge from NDR’s network-centric, behavioral analysis approach.
What Market Gap Does NDR Fill?
Since NDR is such a new solution, it’s useful to place it into a wider context of other security tools. Gartner compares it against some of the multifunction security platforms routinely deployed today, such as Security Information and Event Management (SIEM) and firewalls. SIEM focuses on collecting, normalizing, and analyzing logs from an exceedingly wide range of sources; firewalls, on other hand, track the data packets travelling into or out of an organization’s pre-established networks. While the SIEM provides security teams a single central platform, its lack of a specialized focal point makes it a high-volume alert generator; firewalls, while specific to network security, only
provide north-south visibility. The result is a blind spot around how networks internally share data.
This is the market gap that NDRs aim to patch: standalone NDR tools provide a granularity of network analytics that is otherwise unattainable. Contributing to the market’s 23% YoY growth is an accessible deployment process and the continued development of individual vendors’ features.
Why Is There No NDR Magic Quadrant?
As for the individual vendors that offer NDR tools, Gartner’s usual comparison format is via their Magic Quadrant, which positions technology vendors based on two key criteria: completeness of vision and ability to execute. It then visually maps vendors in a two-dimensional grid divided into four quadrants: leaders, challengers, visionaries, and niche players. At the time of writing, no Magic Quadrant has yet been published for NDR vendors.
While a useful tool for potential NDR customers, it’s important to keep in mind that Gartner only recognized the NDR market in 2020. Since then, they’ve remained focused on annual Market Guides: these assess a market’s new and emerging vendors, compare them with real-world input from Gartner clients, and help establish a solution’s legitimacy and long-term staying power.
Ultimately, Magic Quadrants require a market to reach sufficient maturity, vendor differentiation, and client adoption to enable comparative analysis.
Gartner’s Market Guide to Core NDR Features
Mandatory NDR Features
The following features are absolutely necessary for a tool to meet Gartner’s NDR criteria.
- Comprehensive Traffic Visibility: This feature relies on an NDR’s ability to extract metadata, such as IP addresses, protocols, and payload details, from raw network activity. It’s achieved by sensor deployment across on-prem, cloud, and hybrid infrastructures.
- Bidirectional Monitoring: This is the continuous analysis of both north-south and east-west network movement. Achieved by multi-faceted sensor types, such as network taps for east-west directionality and NetFlow for north-south data.
- Behavioral Detection Techniques: This describes the ongoing identification of anomalies via machine learning and analytics, independent of static attack signatures. Achieved by sending packet metadata to a central Machine Learning algorithm, which can match patterns of collected network behavior to possible attack strategies.
- Baselining and Anomaly Detection: This is the statistical modeling of a network’s behavior over time, with the eventual goal of identifying deviations and flagging suspicious activity. It uses all collected metadata to build a profile of normal, day-to-day network activity.
- Alert Correlation: Rather than flag any deviation from the norm as an alert – which could lead to alert fatigue – Gartner highlights a necessity for NDR to aggregate individual alerts into cohesive incidents. Achieved by an NDR’s algorithm, which must be able to link unexpected network activity to genuine signs of compromise. Often improved through integration with other SOC tools.
- Automated & Manual Response Capabilities: Just as the last feature was critical for the removal of alert fatigue, Gartner underlines how an NDR can’t overly strain a security team’s resources with its response capabilities. The result is a demand for wide-ranging response capabilities: manual responses could be identified within the alert correlation phase, while automated responses may need integration with containment and blocking tools, such as a firewall or IPS.
- Traditional Detection Methods: Finally, Gartner recognizes that behavioral analysis may not be enough on its own: an NDR may also employ IDPS signatures, heuristics, and threshold-based alerts in order to leverage multiple layers of threat verification. This also demands integration with third-party threat intelligence feeds.
Optional NDR Features
With such a range of specific use cases, Gartner also acknowledges the following features that may be optional, depending on different customers’ unique network architectures.
- IaaS Traffic Monitoring: Visibility into infrastructure-as-a-service environments is increasingly vital: some NDR solutions provide this by deploying lightweight sensors within the IaaS environment, which then mirror traffic between cloud workloads.
- SaaS Integration: The weakest point of some NDR tools, Gartner notes that some NDRs allow for traffic to SaaS-based applications to be discovered and analyzed. This SaaS-based application monitoring is most often achieved by API connectors; Microsoft 365 is one particularly popular NDR API integration.
- Log Ingestion & SOC Support: This functionality grants an NDR tool greater flexibility, since it provides a dashboard and associated workflows through which SOC teams can view and investigate alerts. This direct interaction is from the NDR console.
- Full-Packet Capture (PCAP): PCAP files log raw network traffic, capturing every packet’s headers, payload, and metadata. This data can serve as the “ground truth” for network activity, and allow NDRs to rebuild network conversations according to an attacker’s specific tactics.
- However, PCAP isn’t a constant necessity, since it’s immensely high-volume, and it may require a resource-heavy decryption process. As a result, PCAP is positioned as a nice-to-have – and NDR vendors that offer this feature must also have scalability and long-term storage in mind.
- AI-Driven Search Tools: With the rise of NDR dashboards, Gartner has also noted an increased push for AI-assisted search functions. Large Language Model (LLM)-powered smart assistants can allow analysts to query NDR platforms, supporting faster threat hunting and report generation.
- EDR & SIEM Integration: Given that EDR and SIEM both represent deep sources of threat intel, NDR’s integration with them aims to achieve more accurate alert correlation. For instance, NDR’s discovery of lateral movement patterns can be corroborated with EDR’s malware execution alerts from the same timeframe. The resultant cross-referenced alert allows an analyst to delve into an incident far faster.
- Post-Alert Tuning: Since behavioral analysis can increase the rate of false positives, post-alert tuning is essential to ensure NDR becomes a reliable signal source. This is sometimes achieved by PCAP comparison, in which the behavioral model self-verifies, and therefore adjusts its own detection logic. Manual tuning can also be a necessary part of this, with some NDR providers offering one-click options to flag inaccurate alerts.
This comprehensive suite of capabilities ensures NDR systems can serve as both detection engines and orchestrated response hubs. With these features in mind, the Gartner report goes on to establish some key changes in the NDR landscape.
Gartner’s Recommendations for Selecting An NDR
Establish a Workflow
Identify a Common Metric
Given that different NDR platforms rely on a blend of detection techniques – ranging from behavioral analytics to signature-based methods – establishing a common basis for comparison is essential. Evaluating vendors should go beyond feature checklists and focus on the quality and scope of their detection capabilities. Metrics like the “percentage of critical incidents detected by NDR” can provide a meaningful benchmark, helping security teams assess effectiveness across different solutions with clarity and consistency.
Other clear, rationalized metrics could include false positive rates, mean time to classify alerts, or improvements in ransomware detection speed – all of these offer a more grounded basis for cross-vendor comparison.
Determine How False Positives are Managed
Identify Your Automation Requirements
Identify Whether You Need NDR or XDR
Today’s network ecosystems are incredibly diverse – effective NDR strategies ensure a tool coverage that adapts to the specific risks and needs of each environment. With NDR’s evolution into XDR, it’s therefore often necessary to take an analytical view of an organization’s own processes: deep, network-level visibility is uniquely valuable in hybrid and OT-heavy networks. On the other hand, if manual security processes are slowing down the wider system, XDR can offer core NDR capabilities while further consolidating signals from endpoints, identities, email, and networks into a single detection and response framework.
Assess where your threat detection blind spots are. If endpoint coverage is strong but network visibility is limited, NDR may fill a critical gap. If you’re managing multiple siloed tools and struggling with alert overload or slow response times, XDR’s integrated approach could deliver greater value – especially if it can replace and consolidate a defunct tool.
The Rise of Hybrid NDR
The NDR market has already undergone major shifts since its inception in 2020: the sudden rise in remote work that year saw a fresh demand for monitoring network traffic wherever users and workloads exist. As a result, work-from-home arrangements shifted traffic patterns from east-west to largely north-south, and saw the widespread adoption of NDR’s bidirectional analysis.
Converging IT and OT is a major roadmap for some organizations: 2024 saw the significant expansion of NDR capabilities to cover this. And for good reason – NDR is uniquely well-suited to monitoring the activity of Internet of Things (IoT) devices, which cannot support local EDR or IPS software agents. Alongside agentless monitoring, NDR’s protocol awareness also allows it to map OT-specific protocols, such as Modbus TCP, and IT-specific protocols, such as HTTPS, and detail how each interacts across a network.
Other hybrid NDR developments have seen sustained focus on seamless integration with EDR tools. The two tools have individually granular, tightly-constrained focal points, with ML algorithms that are trained solely on each environment’s attack patterns. This common architecture also makes the two solutions highly compatible, and some NDR providers have already started offering both.
What is the Future of the NDR Market?
The future of the market is marked by a dynamic shift toward NDRs becoming more versatile and widely integrated. Rather than remaining standalone tools focused solely on traffic pattern analysis, NDR solutions are increasingly supporting wider swathes of the incident response pipeline.
One key direction is the rise of defense in depth. Here, NDR platforms integrate signature-based detection engines, such as Zeek or Suricata, that are traditionally seen in Intrusion Detection and Response solutions. This modular solution design – and greater number of integrations – sees NDR’s increasing presence as a secondary line of defense.
More groundbreaking NDR vendors are pushing the line between NDR, EDR, and IDS, and building NDR tools that are part of an extended detection and response (XDR) strategy. The integration of network telemetry with signals from endpoint and identity sources is increasingly pushing NDR into the XDR space. This convergence enhances cross-domain detection, enabling more holistic threat visibility. It’s also the underlying reason why some NDR vendors are positioning SIEM tools as competitors, since XDR capabilities are increasingly squeezing out SIEM offerings.
Finally, the emergence of LLM-powered tools positions NDR as a potential front-end solution for security operations, where incident narratives and rapid investigation insights become central to the analyst experience.
As NDR evolves, its trajectory reflects a broader push toward convergence, context, and automation in cybersecurity.
How Stellar Cyber Pushes the Boundary Between NDR and XDR
Stellar Cyber provides NDR and XDR capabilities as part of its unified XDR platform, combining network-focused bidirectional detection with cross-domain threat prevention and response. As an Open XDR, it’s able to deploy NDR sensors, alongside ingesting security and alert data from any other security tooling. It then applies several layers of analysis to coordinate these alerts into complete incidents, including identifying possible MITRE ATT&CK patterns. Finally, automated playbooks allow for threats to be automatically remediated.
As a result, OpenXDR provides lean teams with an in-depth and highly adaptable platform for complete organization-wide security. Explore Stellar Cyber’s accessible dashboards and workflows with a demo today.
