Key Takeaways
- The best NDR solution is not necessarily the one with the longest detection list. Look at what evidence your analysts get after an alert fires.
- Full packets, session content, metadata, flows, and behavioral models are not interchangeable. They support very different investigation workflows.
- AI/ML and behavioral analytics are now common across leading NDR platforms. The bigger differentiators are signal quality, explainability, forensic depth, hybrid visibility, and the ability to respond safely.
- Fidelis Network® takes our top position because it combines behavioral detection with deep session inspection, rich metadata, network forensics, data-aware inspection, and a path into broader investigation and response through Fidelis Elevate®.
The problem with most “best NDR” lists is that by the time you reach vendor number four, everybody sounds the same. None of them tell a CISO which platform the SOC is going to want six months after deployment. So, we are going to approach this comparison differently.
If you are close to choosing a network detection and response solution, you need to look beyond whether an NDR detects lateral movement or command-and-control traffic.
Does the NDR help your analysts prove what happened? Can it reconstruct the session? Can it tell whether sensitive data actually moved? Can it search backward after a new indicator emerges? Can it connect the network activity to an identity, endpoint, cloud workload, or attacker path? And when the SOC finally has enough confidence to act, what exactly can the platform do about it?
Those are the questions behind this ranking.
And since you are reading this on Fidelis, the disclosure is obvious: we believe Fidelis Network® deserves the top position. But pretending that every competing platform is mediocre would make this comparison useless. Several products on this list are exceptionally good at specific things.
The point is figuring out which kind of NDR you are actually buying.
How We Ranked the Top Network Detection and Response Solutions
Our ranking emphasizes the issues we believe matter most once NDR enters production: detection quality, network visibility, depth of retained evidence, investigation and threat-hunting capability, east-west and hybrid coverage, encrypted-traffic strategy, response options, integration into the existing SOC, scalability, and operational fit.
We also looked at something that is often ignored in comparison posts: what the buyer should validate before signing the contract.
Top 10 Network Detection and Response Solutions at a Glance
| Rank | NDR Solution | Strongest Fit | What Stands Out |
|---|---|---|---|
| 1 | Fidelis Network® | Enterprises requiring deep detection, investigation, forensics, and data-aware network security | Deep Session Inspection, 300+ metadata attributes, network forensics, behavioral detection, DLP, sandboxing, broader Fidelis Elevate integration |
| 2 | ExtraHop RevealX | Large hybrid enterprises prioritizing real-time visibility and rapid investigation | High-scale real-time analytics, strong protocol visibility, decryption, behavioral analytics, packet forensics options |
| 3 | NetWitness NDR | Mature SOCs and incident response teams requiring deep network forensics | Full-packet capture, metadata enrichment, session reconstruction, threat hunting |
| 4 | Vectra AI | SOCs prioritizing AI-driven detection and attack-signal prioritization | Behavioral detection, entity prioritization, hybrid network and identity visibility |
| 5 | Corelight Open NDR | Detection engineering and threat-hunting-heavy security teams | Zeek heritage, rich network evidence, open architecture, Suricata integration |
| 6 | Darktrace / NETWORK | Organizations prioritizing adaptive behavioral detection and autonomous investigation | Self-Learning AI, automated investigation, autonomous response |
| 7 | Fortinet FortiNDR | Enterprises already invested heavily in the Fortinet Security Fabric | Behavioral detection, AI/ML analysis, integrated response across Fortinet controls |
| 8 | Cisco Secure Network Analytics | Cisco-centric enterprise networks | Network telemetry analytics, behavioral modeling, encrypted traffic analysis, Cisco ecosystem integration |
| 9 | Stellar Cyber NDR | Teams looking to consolidate NDR into a wider Open XDR operating model | NDR, data lake, correlation, sandboxing, and built-in SOAR |
| 10 | Arista NDR | Network-centric enterprises and organizations requiring IT/OT/IoT entity visibility | AI-driven entity analysis, autonomous investigation, network and asset visibility |
1. Fidelis Network: Best Overall for Detection That Has to Stand Up to Investigation
There is an important difference between knowing that a connection is suspicious and knowing what actually happened inside it. That is where Fidelis Network® earns the top position in this ranking.
Fidelis uses patented Deep Session Inspection® (DSI) to analyze complete network sessions rather than stopping at flow-level information. The platform extracts more than 300 metadata attributes from sessions and combines that context with behavioral analytics and threat intelligence. Fidelis also monitors north-south and east-west traffic and can inspect encrypted traffic when permitted by the decryption policy.
Analysts investigating suspicious SMB traffic need to know more than Host A talked to Host B. They need information about what happened during the session, which protocol activities were made, whether files or commands were involved, if any systems were contacted, and if the behavior is replicating elsewhere in the environment.
Fidelis’ forensic capabilities are designed around that problem. Deep Session Inspection recursively decodes network sessions and can extract artifacts that support attack reconstruction and forensic analysis.
There is another distinction that deserves more attention in NDR comparisons: data awareness. Security teams need to know if any data was exfiltrated. Fidelis Network® includes network DLP capabilities and content-aware inspection designed to identify unauthorized movement of sensitive data. That makes it especially interesting for regulated organizations and security teams where breach investigation, exfiltration, insider risk, and disclosure decisions are part of the NDR use case.
And NDR should not remain isolated. Fidelis Network can operate within Fidelis Elevate®, where network evidence can be correlated with endpoint, deception, threat intelligence, analytics, and response capabilities. Fidelis Deception® also connects network detection, which enables broader investigation and is valuable when an intrusion no longer fits neatly into one telemetry source.
Best fit: Large enterprises, government environments, critical infrastructure, regulated industries, incident response-heavy SOCs, and teams that care as much about investigation evidence as they do about initial detection.
What we would validate during procurement: Size the architecture against real traffic volumes and retention requirements. Also make the vendor spell out which capabilities reside in Fidelis Network® itself and which require additional Fidelis Elevate® modules. A technically strong platform still needs a clean commercial architecture.
2. ExtraHop RevealX: Best for Real-Time Network Intelligence at Enterprise Scale
ExtraHop RevealX would be high on almost any serious enterprise NDR shortlist. Its strength is the speed at which it turns live network traffic into usable operational context.
Current ExtraHop sensors extract more than 5,000 Layer 2 through Layer 7 metrics, and the platform applies behavioral analytics and machine learning to that telemetry. RevealX supports both SaaS and fully on-premises deployment models. In the SaaS model, customers deploy physical or virtual sensors across on-premises and cloud environments while ExtraHop operates the control plane, storage, and cloud-scale analytics. Organizations that require greater data residency or operational control can instead deploy and self-manage the platform on-prem.
ExtraHop is particularly compelling when encrypted traffic visibility matters. The company supports native decryption capabilities, including visibility into Microsoft protocols that are often important during lateral-movement investigations.
The platform is also increasingly positioning network evidence as part of the investigation rather than a separate packet-analysis exercise. For instance, when an alert fires, analysts should not have to open three unrelated tools to figure out whether it matters.
ExtraHop’s current RevealX architecture combines NDR with additional IDS, packet-forensics, and network-performance capabilities, although buyers need to pay attention to which components are core and which are add-ons. Its own datasheet, for example, identifies Packet Forensics as an add-on capability.
Best fit: Large hybrid enterprises that need strong real-time visibility, fast behavioral detection, high throughput, and a polished network investigation workflow.
What we would validate: Exactly how much packet evidence you need to retain and what that does to licensing, storage, and architecture. Confirm whether Packet Forensics is included in the specific RevealX configuration being quoted rather than assuming packet capture or packet visibility automatically means the full forensic capability is part of the base NDR package.
3. NetWitness NDR: Best for Network Forensics-Heavy SOCs
NetWitness deserves the number three position for one simple reason: it takes network evidence seriously.
NetWitness NDR combines full-packet capture with metadata enrichment, behavioral analytics, threat intelligence, network forensics, and session reconstruction. Analysts can move from a detection into the underlying network activity rather than treating the alert as the end product. That is particularly valuable for experienced SOC and DFIR teams.
Metadata can make enormous quantities of network traffic searchable. Full packets can then answer questions that metadata alone cannot. NetWitness explicitly uses this combination to support detection, investigation, validation, and attack reconstruction.
NetWitness also fits organizations that want network evidence connected to a broader security analytics model. Its current platform messaging combines NDR with EDR, SIEM, SOAR, UEBA, threat intelligence, and investigation workflows.
Deep platforms tend to create the most value when the SOC is equipped to use that depth. During a proof of value, do not hand the console to the vendor’s best engineer and marvel at the result. Hand it to one of your analysts.
Can that analyst investigate an unfamiliar alert without a vendor expert standing beside them? How quickly can they pivot through sessions, users, hosts, metadata, and packets? How much administration will the architecture require?
Best fit: Large enterprises with mature SOCs, dedicated threat hunters, network forensic requirements, and incident response teams that routinely need packet-level evidence.
What we would validate: Analyst usability, administrative overhead, retention economics, and how quickly an existing SOC can become proficient with the platform.
4. Vectra AI: Best for Attack-Signal Prioritization
Vectra AI’s strongest argument is not that it uses AI. Its more interesting proposition is the way it attempts to identify attacker behavior across networks, identities, cloud, SaaS, edge, and IoT/OT environments and then prioritize the entities and attack progressions that deserve analyst attention. Vectra calls this approach Attack Signal Intelligence.
This can be extremely attractive to a SOC where the limiting resource is analyst attention.
Instead of asking analysts to treat every abnormal network event as equally important, Vectra’s platform focuses heavily on correlation and prioritization. Its current platform also connects network detections with identity and endpoint context, including integrations designed to place relevant EDR process information beside NDR detections.
Vectra also provides native packet-capture capabilities. Its Selective PCAP feature allows analysts to configure packet captures on individual Vectra Sensors, with completed captures forwarded to the Vectra Brain and retained for up to seven days. That is different, however, from maintaining an always-on, long-term full-packet record of network activity.
For organizations that require continuous full-packet capture and longer-term packet-level forensics, Vectra expanded its alliance with Endace in July 2026. Vectra can now offer Endace Probes directly to customers, combining Vectra’s detection and prioritization capabilities with Endace’s continuous full-packet capture.
If continuous packet evidence and historical breach reconstruction matter to your SOC, determine whether Vectra’s native Selective PCAP meets your requirements or whether the proposed architecture also needs Endace. Then price and size that combined architecture accordingly.
Best fit: Enterprises prioritizing behavioral detection, attack correlation, identity-aware context, and aggressive reduction of analyst noise.
What we would validate: Detection explainability, native PCAP retention requirements, whether continuous full-packet capture requires Endace in your proposed architecture, the resulting storage and licensing implications, and how easily analysts can move from a prioritized attack signal into the evidence needed to validate it.
5. Corelight Open NDR: Best for Detection Engineers and Threat Hunters
Corelight appeals to the team that wants to know what the network is saying, not merely what a vendor’s alerting model decided to surface.
Corelight is built around technologies including Zeek, giving defenders access to rich, structured network evidence. Its platform also integrates detection layers such as Suricata with network evidence and supports an open ecosystem of SIEM, EDR, SOAR, identity, threat-intelligence, and other security technologies.
Corelight has continued expanding beyond its open-source roots. It introduced additional agentic triage capabilities and machine-learning models aimed at detecting tunneling, VPN anomalies, credential abuse, and other evasive post-exploitation behaviors, including analysis of encrypted traffic characteristics without requiring decryption in some scenarios.
Corelight also offers Smart PCAP, which selectively preserves packets relevant to investigations and lets analysts pivot from network evidence into packet data. The approach can extend packet lookback while reducing the storage burden associated with indiscriminate full-packet capture.
For experienced threat hunters, it gives teams room to ask their own questions rather than forcing every investigation through a predefined incident model.
But that raises an important procurement question. How much of the value will come out of the box, and how much depends on the skill of your detection-engineering team?
For the right SOC, flexibility is the advantage. But for the wrong SOC, flexibility becomes shelfware.
Best fit: Detection-engineering teams, sophisticated threat-hunting programs, organizations with Zeek experience, and enterprises that value open network evidence and integration flexibility.
What we would validate: Out-of-the-box detection coverage, investigation experience for Tier 1 and Tier 2 analysts, customization effort, and how much engineering work your desired use cases require and whether Smart PCAP is included in the proposed commercial configuration if packet-level evidence is an important requirement.
6. Darktrace / NETWORK: Best for Adaptive Behavioral Detection
Darktrace / NETWORK uses Self-Learning AI to model an organization’s normal activity and identify deviations across network environments. The platform also uses Cyber AI Analyst to automate investigation and prioritization, while autonomous-response capabilities can act against suspicious behavior.
That can work particularly well in environments where normal behavior is difficult to encode through static rules. Behavioral systems often look impressive during demonstrations because enterprise networks are full of unusual behavior.
Ask a harder question: Can your analysts understand why the platform thinks behavior matters and decide what to do about it quickly? Then introduce legitimate environmental changes and see how the models and analysts cope.
Best fit: Organizations seeking adaptive behavioral detection, automated investigation, and autonomous-response capabilities across complex or changing environments.
What we would validate: Detection explainability, noise under legitimate change, autonomous-response guardrails, and the analyst workflow from anomaly to evidence.
7. Fortinet FortiNDR: Best for Fortinet-Centric Security Estates
FortiNDR makes the most immediate sense when an enterprise already runs substantial Fortinet infrastructure.
FortiNDR combines network traffic analysis with machine learning, behavioral detection, anomaly identification, and malware analysis. FortiNDR can also coordinate mitigation through Fortinet Security Fabric components such as FortiGate, FortiSwitch, and FortiNAC, as well as third-party integrations through APIs.
Fortinet has also been evolving its SaaS-based FortiNDR Cloud offering. Current capabilities of FortiNDR Cloud include behavioral analysis of network activity and newer use cases around AI applications, shadow AI, prompt injection, and non-human activity.
For organizations already standardized around Fortinet, that integration can reduce friction considerably. Response is simply easier when the detection layer already speaks to the enforcement infrastructure.
But this is where architecture should drive the purchase.
If your firewalls, endpoint stack, identity controls, network infrastructure, SIEM, and cloud tooling are predominantly non-Fortinet, make the vendor demonstrate those workflows just as aggressively as the native ones.
Best fit: Enterprises with significant Fortinet deployments that want NDR to participate directly in a broader Security Fabric.
What we would validate: Integration depth and response workflows when third-party technologies are the enforcement points.
8. Cisco Secure Network Analytics: Best for Cisco-Heavy Networks
Cisco Secure Network Analytics, historically associated with Stealthwatch, takes advantage of network telemetry to identify suspicious behavior across enterprise infrastructure.
The platform analyzes network and cloud activity, applies behavioral modeling and machine learning, enriches detections with context, and supports encrypted traffic analysis without necessarily decrypting the content. Cisco also connects Secure Network Analytics with technologies such as Identity Services Engine and its broader security ecosystem.
Cisco continued shipping Secure Network Analytics software updates in 2026, including version 7.6.0, which became generally available in March.
There is, however, an unusually current procurement question to put on the table.
In July 2026, Cisco announced end-of-sale milestones for specific UCS M6-based Secure Network Analytics appliances from December 18, 2026, with migration paths to newer hardware for several affected models. This is an appliance lifecycle transition, not evidence that Secure Network Analytics itself has been discontinued. But an enterprise entering a multi-year agreement should confirm exactly which architecture and appliance generation is being proposed.
That is the kind of question a feature-comparison spreadsheet will never ask for you.
Best fit: Large Cisco environments that can capitalize on existing network telemetry, identity, segmentation, and security integrations.
What we would validate: The exact hardware/software architecture being quoted, lifecycle dates, long-term product roadmap, cloud strategy, and the value proposition in areas of the network that are not predominantly Cisco.
9. Stellar Cyber NDR: Best for NDR as Part of an Open XDR Strategy
Stellar Cyber takes a broader-platform approach. Its NDR capability combines physical and virtual sensors, deep packet inspection, ML-based IDS functionality, malware sandboxing, data storage, automated correlation, and response. The company says its sensors can extract Layer 2 through Layer 7 metadata and files for more than 4000 network applications.
Where Stellar Cyber becomes particularly interesting is what happens outside the network sensor. NDR feeds into a wider platform with a data lake, correlation across network, endpoints, servers, and users, and built-in SOAR capabilities.
That can make a lot of sense for a SOC that is actively trying to consolidate security operations. The buying decision is therefore slightly different.
If you want a pure best-of-breed NDR platform, evaluate Stellar Cyber’s network investigation depth against the specialist vendors.
If you want NDR to become one source inside a broader security operations architecture, the consolidation argument becomes much stronger.
Best fit: Enterprises and MSSPs seeking NDR, correlation, data management, and response within a broader Open XDR model.
What we would validate: Whether you are buying Stellar Cyber primarily for NDR or for platform consolidation. Then test the capability you care about most rather than allowing the breadth of the platform to hide gaps in individual workflows.
10. Arista NDR: Best for Network-Centric Entity and Behavior Analysis
Arista NDR grew from Arista’s acquisition of Awake Security and uses AVA-based sensors and analytics to understand activity across users, devices, applications, IT, OT, IoT, cloud, and unmanaged assets.
The platform processes Layer 2 through Layer 7 network information and uses AI-driven models to identify malicious intent and correlate activity across entities, protocols, time, and attack stages. Arista supports standalone, virtual, cloud-based, and, in some environments, switch-integrated sensor options.
There is a lot to like here for network-centric enterprises.
Asset awareness and entity context are useful when the environment contains devices that will never run an EDR agent.
Arista has also been transitioning some appliance models during 2026. For example, it announced end-of-sale for the DCA-NDR-NCC10 in August 2026 while identifying the DCA-NDR-NB10X as a replacement option. Again, this concerns specific hardware rather than an end to the NDR product, but buyers should make hardware lifecycle part of diligence.
Best fit: Network-heavy enterprises, Arista customers, and organizations requiring visibility across managed, unmanaged, IoT, and OT entities.
What we would validate: Appliance generation, roadmap, cloud architecture, response integrations, and how easily SOC analysts can move from entity-based detection into detailed network evidence.
Which NDR Solutions Vendor Should Make Your Shortlist?
The ranking is useful. Your operating model is more important.
| If Your Priority Is… | Start by Evaluating… |
|---|---|
| Deep forensic investigation and breach reconstruction | Fidelis Security, NetWitness, ExtraHop, Corelight |
| Native network DLP and content-aware sensitive-data inspection | Fidelis Security |
| High-scale real-time network analytics | ExtraHop, Fidelis, NetWitness |
| Behavioral detection and alert prioritization | Vectra AI, Darktrace, ExtraHop, Fidelis |
| Open network evidence and detection engineering | Corelight, Fidelis |
| Existing Fortinet ecosystem | FortiNDR |
| Existing Cisco network and security ecosystem | Cisco Secure Network Analytics |
| NDR as part of broader XDR/SOC consolidation | Fidelis Elevate, Stellar Cyber, Fortinet |
| IoT/OT and unmanaged-asset visibility | Fidelis, Vectra AI, Arista, Corelight, Fortinet |
| Evidence-heavy government or regulated environments | Fidelis, NetWitness, Corelight, Extrahop, Vectra AI |
Frequently Ask Questions
What should a CISO look for in an NDR solution?
A CISO should evaluate network visibility, east-west traffic coverage, behavioral detection, encrypted-traffic handling, packet and metadata retention, threat hunting, forensic investigation, response automation, cloud visibility, integrations, scalability, operational effort, and total cost at production traffic volumes.
The most overlooked criterion is what evidence remains available after a detection.
Is NDR better than EDR?
Neither replaces the other.
EDR provides detailed visibility into activity on managed endpoints, while NDR observes communication across the network and can identify activity involving unmanaged systems, IoT, OT, compromised endpoints, and lateral movement. Using both gives analysts different views of the same attack. For a detailed comparison, read the blog – EDR vs NDR vs XDR
What is the difference between NDR and XDR?
NDR is centered on network telemetry and network-based detection, investigation, and response. XDR correlates signals across several security domains such as network, endpoint, identity, cloud, deception, and other data sources.
Some NDR vendors remain highly network-focused, while others increasingly integrate their NDR capabilities into larger XDR platforms.
Do NDR solutions inspect encrypted traffic?
Approaches vary.
Some platforms decrypt supported traffic when policy and architecture permit. Others use TLS characteristics, flow behavior, statistical patterns, certificates, protocol metadata, or machine learning to identify suspicious encrypted communications without decrypting payload content.
During an evaluation, ask vendors to demonstrate both cases rather than accepting “encrypted traffic visibility” as a simple yes-or-no feature.
Why is Fidelis Network ranked number one?
Fidelis Network combines behavioral Network Detection and Response with patented Deep Session Inspection, rich network metadata, forensic investigation capabilities, network DLP, sandboxing, and visibility into network sessions. Organizations can also connect that network evidence with broader endpoint, deception, analytics, and response capabilities through Fidelis Elevate®.
For enterprise teams that need to move from detection to investigation and evidence, Fidelis is particularly strong.
