Top 9 Use Cases for NDR
Network Detection and Response (NDR) is a cybersecurity tool that focuses on the threat data within your network traffic. Leveraging advanced techniques like behavioral analytics, AI, and machine learning, NDR can identify anomalies and potential security breaches beyond the traditional signature-based approach. NDR enhances traditional security measures by providing in-depth network visibility, real-time threat detection, and automated response capabilities, making it an essential component of modern cybersecurity strategies.
To learn more about what NDR is, see our introduction to NDR. This article will cover key NDR use cases across malware and ransomware identification, illicit command and control prevention, data exfiltration, and its security tech stack consolidation.
To learn more about what NDR is, see our introduction to NDR. This article will cover key NDR use cases across malware and ransomware identification, illicit command and control prevention, data exfiltration, and its security tech stack consolidation.
Gartner Market Guide for Network Detection and Response (NDR)
In recent Gartner® reports on Network Detection and Response (NDR), Gartner notes that OT and IT environments...
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Why Organizations Need Network Detection and Response
NDR solutions play a pivotal role in visualizing and defending your network. In an era where cyber threats are increasingly targeting the connecting fibers of devices, servers, and applications, NDR can see beyond individual application logs. Thanks to this, it can detect and respond to network anomalies, unauthorized intrusions, and other cyber threats that bypass traditional security measures like firewalls and antivirus software.
At its core, NDR leverages advanced analytics, machine learning, and threat intelligence to monitor network traffic. This enables it to identify suspicious activities that could indicate a breach or an ongoing attack. Unlike conventional security tools that rely on known threat signatures, NDR solutions are adept at uncovering novel or evolving threats. This is crucial in a landscape where attackers constantly modify their tactics to evade detection.
The strength of an NDR solution lies in its ability to provide real-time visibility into network activities. It continuously analyzes network traffic, detecting anomalies that could signify a compromise, such as unusual data flows or communication with known malicious IPs. When a threat is identified, the NDR system can automatically initiate a response, such as isolating affected systems, to prevent the spread of the attack.
For those interested in exploring how an NDR solution can be deployed effectively in an enterprise setting, particularly in conjunction with other security tools like SIEM, this resource provides valuable insights into the benefits and practical applications of NDR in a modern cybersecurity framework.
At its core, NDR leverages advanced analytics, machine learning, and threat intelligence to monitor network traffic. This enables it to identify suspicious activities that could indicate a breach or an ongoing attack. Unlike conventional security tools that rely on known threat signatures, NDR solutions are adept at uncovering novel or evolving threats. This is crucial in a landscape where attackers constantly modify their tactics to evade detection.
The strength of an NDR solution lies in its ability to provide real-time visibility into network activities. It continuously analyzes network traffic, detecting anomalies that could signify a compromise, such as unusual data flows or communication with known malicious IPs. When a threat is identified, the NDR system can automatically initiate a response, such as isolating affected systems, to prevent the spread of the attack.
For those interested in exploring how an NDR solution can be deployed effectively in an enterprise setting, particularly in conjunction with other security tools like SIEM, this resource provides valuable insights into the benefits and practical applications of NDR in a modern cybersecurity framework.
9 NDR Use Cases
Network Detection and Response (NDR) is an essential aspect of modern cybersecurity, offering organizations robust defense against a wide array of cyber threats. By analyzing network traffic, NDR solutions detect and respond to anomalies that signify potential breaches or attacks, thus enhancing an organization’s security posture.
Here’s the ultimate list of NDR use cases:
#1. Lateral Movement Detection
Lateral movement refers to a strategy used by attackers in which, after securing initial entry, they stealthily traverse across a network. This is more advanced than the traditional dash-and-grab approach and often allows them to locate specific assets or data while evading detection. This tactic involves advanced methods such as exploiting vulnerabilities in the infrastructure, using pilfered credentials, and sometimes biding time – possibly for months – before making a decisive move post-infiltration.
Recognizing your attack surface is a critical initial step in detecting lateral movement. NDR solutions continuously monitor and analyze network traffic, allowing you to establish a baseline of normal traffic patterns. Thanks to this baseline, they can detect network anomalies such as unusual data flows or access requests to sensitive areas of the network. These can be indicators of lateral movement that appear long before application logs indicate suspicious access. This immediate insight is crucial for limiting the spread of an attack within the network. Upon detecting suspicious activities, NDR systems can automatically initiate responses. This could range from alerting security personnel to automatically isolating affected network segments, helping to contain the breach.
In the event of a breach, NDR tools offer a wealth of forensic capabilities to investigate the incident. This includes tracking the attacker’s movements and methods, which is vital for improving security measures and preventing future breaches.
Recognizing your attack surface is a critical initial step in detecting lateral movement. NDR solutions continuously monitor and analyze network traffic, allowing you to establish a baseline of normal traffic patterns. Thanks to this baseline, they can detect network anomalies such as unusual data flows or access requests to sensitive areas of the network. These can be indicators of lateral movement that appear long before application logs indicate suspicious access. This immediate insight is crucial for limiting the spread of an attack within the network. Upon detecting suspicious activities, NDR systems can automatically initiate responses. This could range from alerting security personnel to automatically isolating affected network segments, helping to contain the breach.
In the event of a breach, NDR tools offer a wealth of forensic capabilities to investigate the incident. This includes tracking the attacker’s movements and methods, which is vital for improving security measures and preventing future breaches.
#2. Compromised Credentials
When credentials are compromised, they may be used in unusual ways – such as accessing data or systems at odd hours, from different locations, or at an unusually high frequency. These anomalies can be cross-referenced against other behavioral indicators to determine the risk likelihood. This is made possible by NDR’s behavioral analytics, which adapts its model to your organization’s typical user behavior patterns. By integrating with other security systems like SIEM (Security Information and Event Management) and IAM (Identity and Access Management), an even more comprehensive understanding of anomalies can be built.
When high-risk credential usage is identified, NDR’s integration with IAM systems can prevent an attack from winding up, and keep your end-users ahead of an attack by switching out credentials.
When high-risk credential usage is identified, NDR’s integration with IAM systems can prevent an attack from winding up, and keep your end-users ahead of an attack by switching out credentials.
#3. Ransomware Attack Mitigation
The process of ransomware infiltration sees attackers exploit vulnerabilities in the network to gain access to computers and servers. Once the ransomware embeds itself within the network, the clock starts ticking: in this critical time-sensitive situation, there are only a few hours until the ransomware irreversibly encrypts large swathes of your data. Historically, the battle against ransomware has unfolded predictably: attackers develop and release new malware; security teams detect this unusual activity and isolate the affected files in post-attack forensics, and new firewall policies are created to prevent a similar attack from happening again. Sometimes, affected parties act swiftly enough to mitigate the damage – but not without placing significant strain on the staff involved. NDR capabilities are instrumental to detecting early signs of ransomware, enabling organizations to respond and prevent payload deployment before the attack reaches the mass encryption phase.
#4. Insider Threat Identification
Insider threats have commonly been a major concern for traditional firewalls and Intrusion Detection System (IDS) evasion. Attackers under the guise of legitimate users and services – experienced enough to steer clear of signature-based detection methods – are some of the most successful threat actors today. Thankfully, even these threats are unlikely to bypass Network Detection and Response (NDR) systems. This is because NDR can identify specific network behaviors that are difficult for attackers to completely avoid.
Furthermore, NDR goes beyond simple rule-based detection: machine learning allows for the continuous analysis and modeling of entity behaviors within the network. This approach allows NDR to contextually spot anything that resembles established attack methods. As a result, even processes that appear legitimate could be subject to scrutiny and flagged if they exhibit unusual characteristics.
However, it’s important to note that not all machine learning systems are equally effective. Systems that utilize the cloud for its speed and scalability in executing machine learning models generally have a significant edge over systems reliant on more constrained local computing resources. This difference can be critical in the efficiency and effectiveness of detecting sophisticated cyber threats.
Furthermore, NDR goes beyond simple rule-based detection: machine learning allows for the continuous analysis and modeling of entity behaviors within the network. This approach allows NDR to contextually spot anything that resembles established attack methods. As a result, even processes that appear legitimate could be subject to scrutiny and flagged if they exhibit unusual characteristics.
However, it’s important to note that not all machine learning systems are equally effective. Systems that utilize the cloud for its speed and scalability in executing machine learning models generally have a significant edge over systems reliant on more constrained local computing resources. This difference can be critical in the efficiency and effectiveness of detecting sophisticated cyber threats.
#5. Malware Detection
The variety of approaches taken by today’s malware is part of the difficulty in defending against it. For instance, the use of top-level domains is a perfect demonstration of attackers’ ability to blend into a sea of legitimate counterparts. NDR solutions offer a way to peek behind malware’s dangerous facades. With multiple machine analysis engines, NDR’s multi-faceted approach models previously established tactics, techniques, and procedures (TTPs), while also conducting deep network packet inspection and metadata comparison.
#6. Phishing Attack Detection
Phishing has long been the method of choice for malware attacks, ever since the widespread use of email. This technique is often the simplest, cheapest, and most direct route for attackers to penetrate the critical areas of your business. NDR systems can mitigate the impact of phishing attacks by identifying suspicious email activities and their consequences on the network.
#7. Command and Control (C2) Communications Detection
C2 communications occur when compromised systems communicate with an attacker-controlled server to receive further instructions or exfiltrate data. NDR identifies communications with known C2 nodes via out-of-bound network mirror ports and virtual taps. By passively capturing network communications, NDR can identify sudden changes in data flow patterns, spot new or unexpected communication channels, and catch irregular data encryption attempts, before an attacker can finish taking advantage of undercooked device protection efforts.
Not only does this analysis also take into account the known characteristics of C2 communications (such as specific data packet sizes, timing intervals, or protocol anomalies), but some NDR solutions can even decrypt and inspect encrypted traffic for signs of C2 communications. This allows for the identification of even advanced attackers that use encryption to conceal their activities.
Not only does this analysis also take into account the known characteristics of C2 communications (such as specific data packet sizes, timing intervals, or protocol anomalies), but some NDR solutions can even decrypt and inspect encrypted traffic for signs of C2 communications. This allows for the identification of even advanced attackers that use encryption to conceal their activities.
#8. Data Exfiltration Prevention
NDR systems use behavioral analytics to understand typical data movement patterns within a network. Any unexpected behavior, like a user accessing and transferring data they normally wouldn’t, can trigger an alert. Thanks to this adaptive understanding of your data landscape, NDR systems can detect patterns that indicate data is being moved inappropriately. These patterns can be a collage of larger-than-normal data transfers, unusual data flows to external destinations, and odd-hour traffic.
Upon detecting potential data exfiltration, NDR systems can automatically initiate responses to mitigate the threat. This might include blocking the transfer, isolating affected network segments, or alerting security personnel.
Upon detecting potential data exfiltration, NDR systems can automatically initiate responses to mitigate the threat. This might include blocking the transfer, isolating affected network segments, or alerting security personnel.
#9. Security Stack Consolidation
NDR solutions are designed to integrate seamlessly with other security tools such as firewalls, IPS, and SIEM systems. This integration creates a more unified security posture by allowing these systems to share data and insights. In turn, your organization benefits from a more comprehensive view of security events across the network, eliminating the need for multiple, disjointed monitoring tools.
Alongside simpler security management, NDR’s advanced analytics can assume roles that would otherwise require separate tools. They provide sophisticated analysis of network traffic and behaviors, reducing reliance on multiple, less advanced systems. While reducing the number of on-the-ground tools necessary, NDR solutions are scalable and adaptable, meaning they can grow with the organization and adjust to changing security needs. This scalability reduces the need for constantly adding new security tools to the stack as the enterprise expands.
By integrating with and enhancing other security tools, providing centralized control, and automating various security functions, NDR effectively consolidates enterprise security stacks, leading to more streamlined and effective cybersecurity operations.
Alongside simpler security management, NDR’s advanced analytics can assume roles that would otherwise require separate tools. They provide sophisticated analysis of network traffic and behaviors, reducing reliance on multiple, less advanced systems. While reducing the number of on-the-ground tools necessary, NDR solutions are scalable and adaptable, meaning they can grow with the organization and adjust to changing security needs. This scalability reduces the need for constantly adding new security tools to the stack as the enterprise expands.
By integrating with and enhancing other security tools, providing centralized control, and automating various security functions, NDR effectively consolidates enterprise security stacks, leading to more streamlined and effective cybersecurity operations.
Automation-Driven Network Detection & Response
Stellar’s solution stands out in the cybersecurity landscape, offering a robust set of NDR capabilities designed to address critical threats at high speed. Our platform excels in real-time detection and response, harnessing the power of advanced analytics, AI, and machine learning to monitor network traffic and identify suspicious activities. Its physical and virtual sensors offer not only deep packet inspection and AI-driven intrusion detection but also provide a sandbox for zero-day attack analysis. These sensors slot in smoothly around the solutions already in your tech stack, while fortifying any previous weak spots.
Discover how our platform can fortify your network defenses, streamline your security operations, and provide the peace of mind that comes with top-tier cybersecurity. To join us in redefining network security, and take a proactive step towards a more secure future, discover more about our NDR platform capabilities.