What are the Best 10 NDR tools?

Published on: November 2, 2022

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24 min read

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For German Version

To defend against the rising number of cyberattacks, businesses use a variety of security solutions to strengthen their cyber defenses and stop hackers from taking advantage of any weaknesses to get into the business network. Traditional security measures like firewalls, IDS/IPS, and SIEM are no longer enough to stop sophisticated attacks like those backed by nation-state actors or carried out by organized criminal groups. Recent data breaches amply demonstrate that such solutions are unable to prevent threat actors. Traditional security solutions also have blind spots, and most of them can't run on Internet of Things devices. This leaves a big hole that cybercriminals can use to their advantage. Network Detection and Response (NDR) security solutions are crucial because they offer enterprises an extra layer of network-level security and threat-prevention capabilities

You need NDR for all of the above reasons because it gives you continuous cybersecurity protection that protects you before, during, and after an incident. Your cybersecurity team will benefit from the automated aspects of NDR since they will save them time and money and give them access to vital real-time alerts and analytics that will help them identify and fix system vulnerabilities before they can be exploited

In this post, we will discuss how to choose a network detection and response solution for your company, as well as the top ten NDR solutions. In addition, we will go through the product's capabilities, important features, strengths and weaknesses, cost, ease of use, and service quality.

How Do You Select a Network Detection and Response Solution for Your Business?

When choosing a network detection and response solution for your business, you need to think about a lot of different aspects. Here are three different combinations to consider for selecting an NDR tool for your organization:

1. Managed detection and response: Managed detection and response as a service include technologies to gather information from your network, detection analytics to identify anomalous activity, and analysts to investigate, confirm, and conduct reaction operations by pre-defined playbooks.

   To determine whether managed services are right for you, ask how the supplier sources and retains threat hunters and analysts.

2. Operated: Operated - In the middle, you'll be in charge of the technology, the people who will use it, and the processes for response, recovery, and recording. Many organizations have evolved in this manner, but they are learning that it is more difficult to sustain.

   To determine whether Operated will best serve you, consider the following questions: What are the resource costs, especially how employing resources for security may influence present initiatives as an opportunity cost?

3. Automated: Automation is at the technological end of the spectrum: SOAR and other approaches use preventive and detective controls and integrate them to perform a technology-determined action.

   To determine whether automated is the best option for you, consider the following question.

   • What is the worst-case situation for a false positive?

   To determine whether managed, operated, or automated is ideal for you, consider the following questions.

   • How fast or easy is deployment?
   • Is the solution capable of ingesting and analyzing all of your data sources?

But to get the most value, buyers should think about three important things when choosing a network detection and response solution for their business.

1. AI and Machine Learning: Stay away from "black box" solutions that largely rely on unsupervised machine learning. These kinds of services provide a substantial amount of operational overhead in the form of false positives and negatives and give the analyst no justification for why anything was reported as a problem.

2. Data: Instead of relying just on NetFlow or IDS warnings, look for solutions that parse the entire packet. Because of the increased depth of visibility, the solution can detect more pertinent threats.

3. Use Cases: Replace current solutions for network forensics, threat hunting, etc. to reduce tool sprawl. Your security activities are consolidated and modernized thanks to this, which increases team productivity.

   Just like with any other security measure, getting a new NDR tool does not automatically make security better. Buyers must consider operational implications when selecting a technological stack.

When choosing an NDR solution, there are a few important issues about the underlying methodology that should be raised:

• How simple is it to trick the detection mechanism?
• Is the AI NDR system wholly or partially rule-based? If so, how much work goes into maintaining and refining the rule set? In the security environment of today, attack vectors change quickly, much faster than rules can be made. Rule-based data can be helpful as context, but it should not be used as the main source of data. The core of the machine learning system should be able to adapt to changes in the network and not be bound by any fixed rules.
• What happens to the network when we add a new subnet or router? Should the NDR system learn everything over again? Learning in a commercial machine learning system can take six to twenty-four months. The methodology is of limited benefit if that cycle keeps happening each time a new element is included in the network. The AI system must automatically adjust to changing network conditions without requiring a lengthy additional learning period
• What is the percentage of false positive detections? What is the rate of false negatives? The response component of NDR heavily depends on the accuracy of the detection. If a subnet is shut down because of a false positive, the network may not work as it should. There are a lot of false positives and false negatives in rule-based systems and systems that use labeling for supervised learning. False positive rates are frequently high in unsupervised systems using clustering and Bayesian techniques.
• Last but not least, effective network detection and response systems should be built to give businesses a clear view of their cyber topography as well as all the strategies and techniques that attackers use to break into networks, take over, and settle in.

The best way to deal with a threat depends on how much information you have, just like the best way to find threats. So, network detection and response systems should put a high priority on giving incident responders the tools they need to act quickly and based on risk. In addition to having the tools and automation required to address issues as rapidly as possible, having visibility into everything from network and cloud traffic to endpoint behavior is essential

The Best 10 Solutions for NDR

The enterprise network attack surface has significantly increased as a result of the broad adoption of digital transformation and related technologies like cloud computing, BYOD, and IoT, exposing new security risks and vulnerabilities. One common misconception is that technology like Endpoint Detection and Response (EDR) systems, Security Information and Event Management (SIEM), and other analogous tools can properly secure a business.

While EDR systems only offer a low-level picture of suspicious processes and interactions within network hosts, SIEMs, on the other hand, have blind spots. A determined attacker may be able to disable or bypass EDR tools. Tools for network detection and response examine network data using non-signature methods like machine learning. They establish a baseline using the data, and when they notice unusual activity, they notify consumers. Since NDR solutions include the ability to take action, they are seen as more than just network traffic analysis. Threat hunting, incident response, and ordering the firewall to drop a suspicious package are a few examples

Due to the abundance of possibilities, selecting the best NDR solution for your business and financial situation is challenging. The best tools for network detection and response are listed below.

1. Arista NDR by Arista Networks

2. Blue Hexagon by Blue Hexagon

3. Cisco StealthWatch by Cisco

4. Darktrace by Darktrace

5. ExtraHop Reveal(x) by ExtraHop

6. IBM QRadar

7. IronNet by IronNet

8. LogRhythm

9. RSA NetWitness by RSA

10. Vectra AI by Vectra

Arista NDR

The Arista security system differs from conventional security since it is built to look like the human brain. Defenders have improved visibility and understanding of what risks are there and how to respond to them thanks to their ability to detect malicious intent and learn over time.

The fundamentals of Arista NDR's delivery of unified zero-trust secure networks improve service quality. Arista's zero-trust networking principles are based on NIST 800-207. The Arista NDR platform examines innumerable data points, detects threats or anomalies, and responds as needed, all in a matter of seconds, for the whole enterprise threat landscape

The ease of use of Arista NDR is extensive. Security teams can quickly and easily view high-risk incidents and compromised entities on a single pane of glass without the need for agents, manual configuration, or difficult interfaces thanks to Arista NDR's seamless interaction with existing security investments

Arista NDR's Product Capabilities can be listed as follows:

• Observe the platform and develop your own understanding of the connections and parallels between entities

• Follow each asset as it travels over the network and looks out for harmful intent among entities.

• Gain a better awareness of each person, device, and application whether they are managed or not

• Automate threat hunting and create specialized detection models for distinct risks to let security analysts contextually address attacks

• Obtain a thorough picture of the enterprise environment's possible attack surface and related business assets

• Identify and comprehend network activity intentions so that the organization's defenses can concentrate on the most serious risks

• Access via detailed, descriptive, and investigative responses that contextualize threats and event specifics

• To take the proper action, gather relevant information about the entities that pose the greatest business risk

• Instead of stopping at alerts, make use of the platform to look into threats independently and give security teams access to the whole event kill chain across organizations, protocols, and time

• To improve current investments, share knowledge with the IT infrastructure and security departments

• The malice intended for each entity can be determined by looking at the evidence that is inevitably related over time

• To give defenders useful evidence, provide forensic artifacts and timings

Arista NDR's Strong Points are listed below.

• Centralized platform: A centralized platform that uses specific AI-driven security detection and response procedures to acquire, process, and store 100 times more real-time network data. Organizations can use the platform to gain a unified understanding of their security posture across hybrid networks.

• EntityIQ: A corporate network's devices, users, and applications can all be identified and profiled using a security knowledge graph

• AVA AI: AVA AI is the first security decision support system in the world to present security personnel with end-to-end scenarios rather than a profusion of pointless alarms.

• Adversarial Modeling: A method using building blocks to convey even the most sophisticated attacking strategies

Blue Hexagon

With the aid of deep learning and artificial intelligence, Blue Hexagon offers a real-time platform that significantly improves our ability to stay on top of current and emerging threats.

Some capabilities of Blue Hexagon are given below:

• The Cloud Security Platform from Blue Hexagon offers enterprises a way forward. With the help of the solution, the customer protects their cloud (cloud visibility, cloud compliance, and threat detection) as well as identify live threats

• Nearly 100% of threats are accurately identified in under a second by Blue Hexagon, which also integrates natively with cloud infrastructure for visibility and enforcement

• Blue Hexagon quickly establishes a connection to your cloud resources utilizing CSP APIs to provide multi-cloud enterprises with an agentless, cloud-scalable SaaS solution.

The service quality and strengths of Blue Hexagon can be explained as follows: Blue Hexagon's cloud security platform can connect to your cloud infrastructure without an agent in just a few minutes by using the cloud service provider's own APIs. It then gathers raw data on resources in every region and account, their configurations, cloud control plane activity, network activity, storage activity, and serverless packages

The Blue Hexagon platform in the middle looks at this raw data with its deep learning models to find strange patterns of behavior in the cloud's control plane and data planes, such as beaconing, command-and-control, and Windows and Linux malware. Also, deep learning models give early access to threat information about IOCs and IOBs, which can be used to look at the raw data. The platform also gives SecOps teams the option to create their own detection-as-code (e.g., to identify specific MITRE ATT&CK behaviors) to supplement or correlate with the platform's native detections.

Six specific results are produced for DevOps and SecOps teams as a result of the ingestion, analysis, indexing, and deep learning judgment on the raw cloud data

Blue Hexagon finds hundreds of misconfigurations with over 100 different services across AWS, Azure, GCP, and OCI. It also lets you see what's in your inventory and what's going on in the cloud, and it helps you meet many standards, like CIS, HIPAA, and PCI. The 12 out of 20 CIS-recommended controls that Blue Hexagon covers

The simplicity of use for Blue Hexagon includes: Blue Hexagon's cloud security platform can connect to your cloud infrastructure without using agents. It does this by using cloud-native APIs to gather information for security analysis. As an illustration, Blue Hexagon will continually import all AWS CloudTrail, VPC Flow Log, VPC Traffic Mirroring, configuration, and S3 transaction data

In order to provide visibility, hunting, and alerting across various clouds, multiple locations, and numerous accounts, this raw data is enriched, consolidated, and indexed in a single SaaS interface.

The system's output, such as security findings and configuration errors, can subsequently be forwarded to several response tools. These response tools are SIEM, perimeter, workflow/collaboration, and endpoint.

• SIEM: Security discoveries and accompanying raw metadata can be uploaded to systems like Azure Sentinel, Splunk, or AWS Security Hub for additional analysis or correlation with other tools

• Perimeter: IOCs obtained from security discoveries, such as malicious IP addresses, domain names, or hashes, can be sent as rules to perimeter security solutions.

• Workflow/Collaboration: Security discoveries can be added to collaboration tools like Slack or ticketing tools like Jira for additional investigation or correction.

• Endpoint: To avoid attacks, security information about rogue or malicious network entities or infected assets can be provided with EDR or EPP solutions.

Cisco StealthWatch

Scalable security analytics and visibility throughout your organization with industry-leading machine learning and behavioral modeling offered by Secure Network Analytics, you can outwit new dangers in your digital business (formerly Stealthwatch). Utilize telemetry from your network architecture to learn who is using the network and what they are doing. Identify sophisticated threats and take prompt action to counter them. Improved network segmentation will help you protect important data. Use an agentless solution that expands with your organization to complete all of this.

The main capabilities of Cisco StealthWatch are as follows:

• Obtain thorough analytics and visibility: Find threats across a dynamic network using high-fidelity warnings that are enhanced with contexts like users, devices, locations, timestamps, and applications. Examine encrypted traffic for threats and compliance without decrypting it.

• Accelerate incident response and forensics: Utilize advanced analytics to quickly identify new malware and insider risks, including data theft, policy violations, and other sophisticated assaults.

• It reduces network segmentation complexity: Smarter segmentation policies can be defined without disturbing the business. Create personalized alarms to identify unauthorized access and ensure compliance.

• This increases your visibility in public clouds: Secure Cloud Analytics provides SaaS-based visibility and threat detection across all major public cloud platforms without the use of software agents.

The use of the Cisco StealthWatch is very simple. It offers flexible deployment options for all-around visibility. In addition, Cisco StealthWatch features hardware or virtual appliances, granular tuning, SecOps, and NetOps use cases, and air-gapped networks.

Among Cisco StealthWatch's additional user-friendly capabilities are simple deployment, automated tuning, SecOps, and light NetOps use cases, as well as monitoring Meraki and container environments where SaaS-based Cisco StealthWatch is used.

In addition, Cisco StealthWatch is suitable for all companies that use serverless environments as their public cloud architecture, such as Microsoft Azure, Google Cloud Platform, or Amazon Web Services.

The advantages of Cisco StealthWatch can be explained as follows: Cisco Secure Network Analytics, which makes use of business data from the current network architecture, is the most comprehensive visibility, network traffic analysis (NTA), and network detection and response (NDR) solution. It uses multi-layer machine learning and asset modeling to find threats faster, respond to them more quickly, and make network segmentation easy. You will always be aware of who is on your network and what they are doing thanks to powerful behavioral analytics.

A unified agentless system lets you see the whole network, from what's on-premises to what's in the cloud. Also, it is the only known solution that uses encrypted traffic analytics to make sure that policies are followed and to find malware in encrypted data without having to decrypt it. The Cisco SecureX platform extends the value of Secure Network Analytics even further, spanning the network and cloud to endpoints, applications, and more.

You can benefit from the training opportunities offered to you by the Customer Success Learning Services team. To improve the deployment of your solution and take care of specific business requirements, you can work with the Professional Services team. The team of customer care representatives is available 24/7 to assist you with implementing, debugging, and managing the solution .

Endpoint-based pricing is available. There is usage-based pricing, which is based on the amount of log data.

Darktrace

Darktrace DETECT looks at a lot of different factors to find small changes that could mean a growing threat, like new malware or methods that haven't been found yet. It is an NDR solution that recognizes attacks that ordinarily go unnoticed and distinguishes between malicious and benign activities

That explains why Darktrace is simple to use. First off, whether implemented throughout the entire organization or in specific coverage areas like email, Darktrace's installations happen rapidly. In roughly a week, Darktrace Self-Learning AI learns the routines of your business and becomes more customized with each passing second

Second, data from Darktrace DETECT is sent into Darktrace RESPOND for ground-breaking AI-powered security that neutralizes attacks that could disrupt your operations instantaneously, and autonomously, and is built to support your security team.

Contrary to conventional AI, Darktrace's quality of service is unique. Traditional artificial intelligence (AI) often relies on identifying risks based on past attack data and documented methodologies, necessitating the cleansing, labeling, and moving of data to a central repository. The Self-Learning AI in Darktrace DETECT continuously improves its understanding as your environment changes by learning "on the job" from real-world data. By identifying vulnerabilities and strengthening your defenses, Darktrace lowers your cyber risk.

The major capabilities of Darktrace are given below:

• Darktrace has total awareness of the entire digital estate. Millions of data points and cutting-edge AI algorithms influence precise detection.

• In 2023, Darktrace will introduce a capability that will allow your systems to recover after a cyberattack and return to normal operation.

• The significance of compromised files is promptly evaluated by Darktrace before, during, and after an attack.

• Darktrace finds crucial nodes in computer networks using graph theory.

• Darktrace uses correspondence semantics to find and stop misdirected emails.

• Darktrace makes meta-scoring-based autonomous detection of a business inbox's intended purpose so that it is aware of which business inboxes should receive a lot of emails and which should not.

• Darktrace uses crypto mining credentials to identify insider risks and distinguish them from widespread malware.

• Darktrace maximizes the visibility, security, and utilization of diverse, complex cloud and SaaS systems.

• Darktrace is a tool for monitoring network activity and spotting covert cryptocurrency mining.

ExtraHop Reveal(x)

Providing complete east-west visibility, real-time threat detection inside the perimeter, and intelligent reaction at scale, ExtraHop Reveal(x) Enterprise is a breakthrough in network detection and response (NDR).

Extrahop's capabilities are explained below:

You can concentrate on the risks that matter and stop breaches 84% faster with ExtraHop's cloud-native network detection and response.

Automate the discovery and identification of all enterprise devices, including unmanaged and IoT ones. Real-time monitoring of all workloads and East-West and North-South transactions in AWS, Azure, and Google Cloud Line-rate decryption of SSL/TLS 1.3 encrypted traffic provides comprehensive coverage, allowing you to detect rogue devices, suppliers "phoning home" important data, and insider threats

Use cloud-scale behavioral detection, which is powered by millions of ML models and thousands of network signals, to catch advanced activity after a breach, such as lateral movement, command and control, and data exfiltration. Detect the whole

ExtraHop Reveal(x) has different dimensions of quality of service. To maintain the accuracy and precision of its machine learning, ExtraHop Reveal(x) network detection and response automatically discovers and categorizes every transaction, session, device, and asset in your enterprise at up to 100Gbps by decoding over 70 enterprise protocols and extracting over 5,000 features. With Reveal(x) 360, ExtraHop extends SaaS-based network detection and response to the cloud.

Moreover, ExtraHop Reveal(x) allows you to fully detect late-stage attack activities by leveraging ML-based behavior, rules, and custom triggers. This way, you will always know what devices are active in your network and can automatically detect new, rogue, and unmanaged devices.

ExtraHop Reveal(x) has varying ease of use. With just one click, you can get contextual evidence and intelligent reaction options in ExtraHop Reveal(x). This makes it easy to validate and remediate threats quickly.

Second, Reveal(x) automatically sorts devices into highly specific behavioral peer groups so that it can detect odd behavior with the fewest false positives. By auto-discovering and classifying everything that talks on the network, Reveal(x) ensures an always up-to-date device inventory without manual effort.

For simpler triage and reaction, Reveal(x) contextualizes detections from an entire transaction with threat intelligence, risk scores, and asset criticality.

Powerful integrations with products like CrowdStrike, Phantom, Demisto, and Palo Alto Networks enable you to automate remediation while Reveal(x) handles detection and investigation.

In minutes or hours rather than days, validate, prioritize, and identify the root cause. Automated response using orchestration, firewalls, and trusted endpoint partners. ExtraHop reduces time-to-resolution by making investigations as simple as a few clicks and integrating automatic response tools to lower MTTR, prevent data breaches, and aggressively drive out attackers

For the hybrid enterprise, ExtraHop offers total visibility, real-time detection, and intelligent response, so you can create your security the same way you build your business cloud-first

By analyzing all network interactions in real-time, including all cloud transactions and SSL/TLS encrypted traffic, it provides complete insight within the perimeter and throughout the hybrid attack surface. ExtraHop uses cutting-edge machine learning to safeguard your cloud investment, ensure the delivery of vital apps, and assist you in identifying risks in the east-west corridor

Regardless of how your company engages with the outside world, ExtraHop offers a solution to assist you in safeguarding your assets wherever they are

At ExtraHop, three characteristics, cloud-delivered, cloud-agnostic, and cloud intelligent, are necessary to be a genuinely cloud-native NDR solution provider. The first and only cloud-native NDR platform, Reveal(x) Cloud, provides immediate benefits through situational awareness and 360-degree visibility, which work together to provide continuous protection across the full attack surface.

IBM QRadar

By monitoring network behavior in real-time, IBM Security QRadar Network Detection and Response (NDR) assists your security teams to provide meaningful insights and reactions, it blends depth and breadth of visibility with high-quality data and analytics

Using IBM QRadar is simple.

• Become aware of odd activity: Threats might often go undetected because of the large amount of data that is transferred over your network. Reconnaissance, pivoting, and device transfers-all signs of malicious lateral movement-should be caught in real-time

• Quick detection cuts down on dwell time: Data is frequently stolen in small, irregular quantities by patient attackers. Find sensitive information that is being transferred over your network in real-time via email, chat, file uploads, downloads, or social media.

• Update resources automatically to stay one step ahead of attackers: As new devices join your network, you may see them. Profile assets continuously based on characteristics and behavior to find threats, compromised hardware, and shadow IT.

• From being reactive to being proactive: To help stop future attacks , query historical network activity to look for past activity, identify odd behavior, and identify the assets involved.

Three features of IBM QRadar represent the quality of service:

1. Take away blind spots: By merging event and flow data from on-premises and cloud settings, you may have thorough, real-time visibility for better network detection and response.

2. Quicker danger detection: Establish a baseline of typical network activity using machine learning-based analytics to swiftly spot abnormal behavior before attackers interrupt the system

3. Leverage current investments: Enable comprehensive threat visibility, detection, and response in a single solution to help reduce tool switching and leverage and scale security investments

The major characteristics of IBM QRadar are explained below:

Threats lurk within the regular traffic on your network. Obtain a comprehensive network view across a variety of network devices.

Real-time network data analysis and correlation. Insights into the network allow for session reconstruction, complete packet capture, critical metadata extraction, and application analysis.

Base lining for typical network activity, looking for anomalies, and seeing suspicious behavior will help you spot minute variations in user or system behavior that could have gone unreported in the past.

By seeing malicious activity and enabling your security team to find domains that are being accessed from inside your network using Domain Generated Algorithm (DGA), Tunneling, or Squatting, you can gain insight into your local DNS traffic.

By reconstructing data and retracing actions, you may trace the exact steps taken by online offenders. It records, recreates, and plays back the full sequence of events.

When no other network packet capture (Network PCAP) device is deployed, QRadar Network Packet Capture provides an optional appliance to store and manage data utilized by QRadar Incident Forensics.

Customers have access to a variety of pricing choices through QRadar NDR:

• Usage-based pricing: This straightforward, expandable option enables you to start small with the initial users and capabilities and scale quickly as more users, features, and data are added.

• Enterprise-wide pricing: Enterprise-wide pricing is determined by the size of your company's overall IT infrastructure or the quantity and variety of data sources that need to be protected.

• Appliance-based pricing: With this choice, you can simply extend deployment by adding additional appliances after starting with just one.

IronNet

IronDefense is the most cutting-edge network detection and response (NDR) platform on the market, designed to thwart the most complex cyber threats.

IronDefense, an innovative NDR solution, increases detection efficacy within your network environment while enhancing visibility throughout the threat landscape. As a result, your SOC team can utilize the current cyber protection tools, resources, and analyst capacity more effectively.

These 3 features demonstrate IronNet's quality of service:

• Full discernibility: With the combination of IronDome Collective Defense, real-time insights into the danger landscapes of various industries, human insights to identify threats, and higher-order analysis of anomalies associated across peer groups

• Quicker reaction: To prioritize detected signals based on risk and supplement the nation's limited cyber staff, advanced automation will be used to apply reaction playbooks created by the nation's top defenders

• Sophisticated behavioral detection: Advanced network behavioral analysis, which makes use of tried-and-true AI/ML and analytics to protect extremely secure networks, enables analysis to be scaled up to the largest companies.

Other features of IronNet are as follows:

• IronDefense employs tested analytics based on ML and AI methods used in actual defense against highly skilled cybercriminals and threat actors at the level of nation-states

• IronNet's alert correlation engine pre-correlates anomalous activity by threat categories and models adversarial attack strategies to increase risk scoring and alert prioritization while significantly decreasing alert load and investigation time

• For analysts' convenience, IronNet provides prolonged hunt support windows of 30, 60, and 90 days

• IronDefense uses optional streaming analytics to find malware payloads on your network. To assess if a payload is malicious, these analytics are cross-referenced with a file reputation database

• To provide dynamic, real-time visibility to threats targeting your supply chain, industry, or area, IronDefense integrates with our IronDome Collective Defense solution

• IronNet collaborates with each of its clients to provide a tailored experience that aids in the planning, implementation, integration, and administration of IronDefense by your security team

• With the ability to support your scattered teams, IronDefense uses a wide variety of cloud-deployed sensors for public/private cloud, virtual networks, and on-premise networks to help you safeguard your special infrastructure

• By ingesting north-south traffic at your network perimeter and east-west traffic within your business, IronDefense can offer complete visibility across your network and full insights at the individual session level. IronDefense uses portable virtual and physical sensors and data collectors.

Flexible prices and packages are available to meet your business's needs.

• Basic: For enterprises of all sizes that require sophisticated log-based behavioral detection and collective protection, the monthly fee is $3 per employee.

• Professional: For businesses that need market-leading network detection and response, collective defense, and reporting use cases, the monthly cost per employee is $6.

• Enterprise: $9 per employee per month for large businesses with significant data volumes, many network detection use cases, and additional services like reporting, cyber hunting, and industry-leading network detection and response.

LogRhythm

An NDR solution called LogRhythm analyzes network, user, and host behavior using hybrid analytics, which combines machine learning, rules-based detection, and threat intelligence. The ability to detect lateral movement, exfiltration, malware compromise, ransomware, and other threats in real-time is made possible by the holistic approach, which offers a true depiction of all activities within the company domain

You may handle new security use cases for desktops, supply chains, data centers, public clouds, and IoT/OT with the aid of LogRhythm NDR. The SaaS-based threat detection solution can be used independently or in conjunction with the LogRhythm SIEM Platform to swiftly identify attacks and reduce the risk to your company.

Mesh computing is used by LogRhythm NDR, which is powered by patent-pending TensorMist-AITM technology, to increase data collection and analytics and reduce operational costs.

Key features of LogRhythm NDR are as follows:

• Actor and action identification in real time: It enables you to detect threats including lateral movement, exfiltration, malware compromise, and ransomware in real-time by providing end-to-end corporate activity at the network, host, user, and process level.

• Integration: Integration with firewall and enhanced detection and response (EDR) systems improve your threat detection by adding network visibility to cover endpoints, data centers, and the cloud.

• Cloud agentless collection: By ingesting cloud data, Cloudera models the characteristics of the operating system and the workload across virtual machines, Kubernetes, and containerized systems. TensorMist-AI expands data collection and analytics while reducing bandwidth costs by using mesh computing.

• A thorough and precise threat detection: It prevents sophisticated assaults and more than 90% of false positives are reduced. Smart threat hunting of tactics, techniques, and threat groups across numerous attack vectors is provided via the built-in MITRE ATT&CK Engine.

• Simple deployment: With our cloud-native security stack and out-of-the-box integrations for current firewall and EDR systems, getting started is simple.

The following is a list of the characteristics that make LogRhythm NDR simple to use.

Tensor-Mist technology from LogRhythm NDR prevents data from moving between clouds in addition to offering quicker, more scalable threat detection, response, and hunting. This feature enables your business to gather and enhance massive amounts of security data "on location".

The best SaaS and cloud models are made possible by mesh-network analytics and processing as well as reliable SaaS delivery. This model is scalable and maximizes value and operating costs for network threat detection.

LogRhythm sees the whole range of workloads, including serverless functions down to individual containers and Kubernetes clusters, and detects unwanted data flow from your cloud environments.

EDR integrations support deployments of SentinelOne, VMware Carbon Black, and CrowdStrike. For log collecting, LogRhythm NDR also interacts with industry-leading firewalls like Palo Alto Networks. At the LogRhythm NDR console, analysts may configure these integrations in a matter of minutes.

With the one, user-friendly console from LogRhythm NDR, you can cut your annual spending and appliance costs in half.

A built-in MITRE ATT&CK Engine and a machine learning (ML)-driven network threat detection and response solution are provided by LogRhythm NDR, which closes blind spots and continuously monitors the network of your company.

RSA NetWitness

An NDR solution called NetWitness Network quickly identifies and counters network threats. Some features of NetWitness Network are as follows:

• Reduces the alert tiredness of analysts: To identify high-priority attacks and minimize false positives, NetWitness Network supplements log data with contextual information and threat intelligence.

• Facilitation of network data management: Thanks to pervasive visibility, data administration, and analysis across your entire IT environment are made simpler.

• Accelerates the detection and response to network threats: Faster network threat detection, research, and forensics are made possible by NetWitness Network's rapid, comprehensive network visibility.

• Investigate and detect threats more easily: In addition to sophisticated automated detection, investigation, and forensics tools, NetWitness Network also provides simple data visualizations and nodal diagrams.

Using the NetWitness Network is simple. To create metadata that significantly speeds up alerting and analysis, NetWitness Network dynamically parses and enriches log data at the time of packet capture

Different characteristics of the NetWitness Network show the quality of service:

• Dependable forensics abilities: The NetWitness Network combines sophisticated, integrated forensic investigation tools with an in-depth examination of hundreds of protocols.

• Support for native decoding: The NetWitness Network, which offers native decoding and integrates with third parties to give extra support for decryption, is unaffected by encoded traffic.

• Comprehensive infrastructure-wide visibility: NetWitness Network offers real-time visibility into all of your network traffic, whether it is being used locally, in the cloud, or across multiple virtual environments. The NetWitness Network identifies known and unidentified attacks that endanger enterprises using a special blend of behavioral analytics, data science methodologies, and threat intelligence.

• Visibility in the increasingly digital environment: The NetWitness Network, which can centrally monitor network traffic for threats from any source and deploy collection components on-premises, virtually, across hybrid architectures, or entirely within public clouds, is the best fit for the ever-expanding digital landscape. The analysis of data across remote and virtual environments is made easier by ubiquitous network visibility, which enables quick identification and action.

Vectra AI

Vectra threat detection and response is a comprehensive cybersecurity platform that collects, recognizes, and prioritizes security alerts. The Cognito platform for Network Detection and Response (NDR) is used to identify and stop attacks inside clouds, data centers, the Internet of Things, and enterprise networks. For low-level threats, the platform also offers automated reaction capabilities, and it escalates more serious abnormalities to security staff.

Cognito gathers information from various relevant sources, and then adds context and security knowledge to it. In data centers, IoT, or enterprise networks, it begins by putting sensors across several networks. Useful metadata is extracted by the algorithm from network and cloud traffic. The data may also include non-security data that aid in investigations.

To enable crucial use cases like threat detection, investigation, hunting, and compliance, the data is enhanced with security context The platform's machine learning foundation enables it to adapt to every new threat scenario. It uses identification and host-level enforcement to identify, group, prioritize, and foresee assaults.

A person can investigate 50 hazards using the Vectra platform in about two hours. It produces quicker outcomes by prioritizing warnings and utilizing threat intelligence. One of Vectra's strengths is the emphasis it places on fusing research and data science for security insights. With unsupervised, supervised, and deep learning models, it allows behavior codification.

The main features of Vectra AI are listed below:

• Threat detection and reaction powered by AI

• Attacks using behavior-based threat detection in real-time.

• It detects dangers by combining and correlating thousands of events.

• It provides data science security insights and a chain of evidence to enhance threat investigation

• Deep learning and neural networks are two examples of machine learning approaches.

• It gives insight into online criminals and examines all network activity.

• Regular upgrades with fresh threat detection techniques.

• It offers both at-rest and in-transit encryption. It provides AES-256 encryption for the AWS version through the AWS Key Management Service.

• Guaranteed accessibility in accordance with the chosen service's SLA.

• It does not connect to networks in the public sector.

Different characteristics of Vectra AI show the quality of service.

• Behavioral models are used to help identify unknown attackers.

• Vectra AI prioritizes the most pertinent information to enable proactive action. This gives investigators a clear image and a wide-ranging framework, and this helps in the incident response process' decision-making. Moreover, it helps when working with large datasets by mass-collecting metadata and automating laborious analysis. On account of this, this reduces the amount of work that security experts must do to look into threats.

• Vectra services also have the benefit of being deployable in a hybrid, private, or public cloud. Support can be contacted by email or online ticket, and responses typically take four hours. 24/7 phone support is offered.

• Vectra offers comprehensive on-site, online, and documentation support. It supports a variety of web browsers, including Internet Explorer, Microsoft Edge, Firefox, Chrome, Safari, and Opera, when it comes to the user interface. It is not, however, compatible with mobile devices.

A free trial is offered along with a subscription-based pricing structure.