Highly performant NDR solutions use advanced machine learning and artificial intelligence tools to model adversary tactics, techniques and procedures that are mapped in the MITRE ATT&CK framework to detect attacker behaviors with high precision. They surface security-relevant context, extract high-fidelity data, correlate events across time, users, and applications to drastically reduce time and effort spent in investigations. They also stream security detections and threat correlations to security information event management (SIEM) solutions for comprehensive security assessments.
NDR solutions move beyond merely detecting threats, responding to threats in real-time by native controls or by supporting a wide-range of integrations with other cybersecurity tools or solutions like security orchestration, automation, and response (SOAR).
Network Detection and response (NDR) is a cybersecurity solution that continuously monitors an organization’s network to detect cyber threats & anomalous behavior using non-signature-based tools or techniques and responds to these threats via native capabilities or by integrating with other cybersecurity tools/solutions.
NDR plays a pivotal role in securing your digital infrastructure.
Threat history is generally available in three places: network, endpoint and logs.
Security teams that deploy these tools are empowered to answer a broad range of questions when responding to an incident or hunting for threats.For example, they can answer: What did this asset or account do before the alert? What did it do after the alert? Can we find out when things started to turn bad?
For example, exploits that operate at the BIOS level of a device can subvert EDR or malicious activity may simply not be reflected in logs.
But their activity will be visible by network tools as soon as they interact with any other system through the network.
Or advanced and sophisticated attackers use hidden encrypted HTTPS tunnels, that blend in with regular traffic, to launch a command and control (C2) session and use the same session to exfiltrate sensitive business and customer data and evade perimeter security controls but NDR solutions are extremely adept at detecting these behaviors.
Effective AI-driven network detection and response platforms collect and store the right metadata and enrich it with AI-derived security insights.
Effective use of AI can then drive the detection of attackers in real-time and perform conclusive incident investigations.
Network Detection and Response cybersecurity solutions provide continuous visibility across all users, devices and technologies connected to the network, from data center to the cloud, from campus users to work from home users, from IaaS to SaaS, and from printers to IoT devices.
Leading NDR solutions use behavioral analytics and ML/AI to directly model attacker behaviors and detect advanced and persistent attacks with surgical precision. They avoid the deluge of low-fidelity and uninteresting alerts since they don’t detect anomalies, but rather, detect active attacks. They provide detection coverage for several phases of an attack lifecycle, including persistence, privilege escalation, defense evasion, credential access, discovery, lateral movement, data collection, C2 and exfiltration.
Leading AI-driven NDR solutions are automatic and dramatically improve security detections and security operations center (SOC) operational efficiency despite organizations and teams being plagued by a chronic shortage of cybersecurity expertise & personnel by offering full attack reconstructions in natural language that provide analysts, all the information they need to act on alerts quickly and completely.
In addition to detecting sophisticated attacks that operate discreetly and employ evasive techniques, NDR solutions offer the ability to automatically respond to serious attack via native controls and shut down an attack in real-time. Additionally they integrate with several cybersecurity products like EDR or cybersecurity solutions like SOAR.
IDS were the first generation of NDR solutions. They used rule-based and signature-based detection to identify known threats. IDS were effective at detecting common attacks, but they were also prone to false positives and could be easily evaded by attackers.
Next-generation intrusion detection systems (NGIDS) were developed to address the limitations of IDS. NGIDS used a combination of signature-based detection, anomaly-based detection, and behavioral analysis to identify both known and unknown threats. NGIDS were more effective at detecting sophisticated attacks than IDS, but they were still complex and difficult to manage.
NDR solutions take the capabilities of NGIDS to the next level. They use AI and machine learning to analyze network traffic and identify patterns and anomalies that may indicate an attack. NDR solutions can detect a wide range of threats, including known and unknown malware, intrusions, and data leakage. NDR solutions are also easier to manage than NIDS and NGIDS.
The evolution of NDR is driven by the increasing sophistication of cyberattacks. As attackers develop new techniques, NDR solutions must evolve to keep up. AI and Machine Learning play a critical role in the modern NDR solution, enabling it to detect and respond to threats that would be difficult or impossible to detect using traditional methods.
Managed Network Detection and Response (NDR) is a service that leverage the expertise of a specialized cybersecurity team or service provider to continuously monitor their network traffic, analyze patterns, and identify potential security threats.
The key components of Managed NDR may include:
By outsourcing the responsibilities of network detection and response, organizations can benefit from the expertise of cybersecurity professionals, stay updated on the latest threats, and ensure a proactive approach to defending against evolving cyber risks. This approach is particularly valuable for organizations that may lack the in-house resources or expertise to effectively manage their network security.