NDR Network Detection & Response

Network Detection & Response is now considered an indispensable means of securing corporate networks.

What is Network Detection & Response?

NDR (network detection and response) is a solution that adds context to security threats. Features such as network traffic analysis and the real-time inspection of network communications allow NDR solutions to detect and investigate threats, anomalous behaviours and risky activity across all the corners of your network. NDR acts as a virtual forensic expert that has the capability to understand the exact scope and peculiarities of a security incident or breach.

NDR solutions harness the strengths and virtually unlimited capabilities of high-end AI, machine learning and deep learning to provide predictive risk analysis. When you are dealing with large amounts of poorly contextualised alarms, NDR is often a better fit than SIEM.

The solutions typically provide centralised, machine-based network traffic analysis and response solutions, including efficient workflows and automation. The positioning in the network and help from machine learning provides a full insight and analysis of the network in order to identify and eliminate lateral movements in particular.

  • Scope: Network and inter-device traffic
  • Intention: Visibility/transparency of network traffic, detection of known and unknown threats and lateral movements, alerting and response
    Methods: Indicator of Attack (IoA), anomaly detection, user behaviour, machine learning
    Challenges: Advanced attacks and intrusions, malware-free attacks

Capabilities of NDR Solutions

NDR solutions analyse network traffic to detect malicious activity inside the perimeter—otherwise known as the east-west corridor—and support intelligent threat detection, investigation, and response.

Using an out-of-band network mirror port or a virtual tap, NDR solutions passively capture network communications and apply advanced techniques, including behavioral analytics and machine learning, to identify both known and unknown attack patterns. This data can also be used to perform real-time investigation into post-compromise activity and to forensically investigate incidents. While not all NDR solutions decrypt network traffic, the most advanced solutions provide secure decryption capability to help identify threats hiding within encrypted traffic.

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What to look for in an NDR solution

Contextual networkwide visibility

Without contextual networkwide visibility, security teams are essentially blind. NDR solutions must provide a comprehensive view into all enterprise devices, entities, and network traffic. They must monitor and analyse all traffic flows in real time and monitor and analyse not only traffic that enters and exits the environment, but also all traffic that moves laterally across the network.

Deploying an NDR tool with context-rich visibility provides a full picture of network activity. Security teams can see which users are on their network, what devices they are interacting with, where they are accessing the network from, and what kind of data they are sharing. This visibility enables them to not only detect threats but also determine their source, where else they may have propagated, and which users have been compromised. It also provides other useful forensic information such as a user’s location, device type, event time stamps, and more.

As organisations move to a cloud-first strategy, NDR solutions should also provide visibility in multiple cloud environments

Behavioral, non-signature-based detection techniques

Non-signature-based advanced analytical techniques, such as machine learning and behavioral modeling, establish a baseline of what normal network activity looks like. NDR tools should be able to quickly identify and issue alerts related to suspicious traffic deviating from the normal range that traditional signature-based tools miss. Examples include if an attacker is using lost or stolen credentials to gain access or if a malicious employee is involved in hoarding and/or exfiltrating sensitive data.

With nearly 75 percent of all network traffic being encrypted, NDR solutions also should be able to analyse encrypted traffic without decryption and detect threats that attempt to cloak themselves in encrypted traffic. In addition, NDR solutions should correlate global threat intelligence to local threats to thwart attackers that attempt to infect multiple victims with the same malware.

Accelerated threat response

By combining context-driven, enterprise-wide visibility and advanced analytical techniques, NDR tools should be able to pick up on early signs of attacks. Their advanced threat detection capabilities should, for example, identify unusual remote access, port scanning, the use of restricted ports or protocols, etc.

Best-in-breed NDR solutions provide high-fidelity alerts prioritised by severity, automated response capabilities to save teams time, and manual response capabilities to enhance threat hunting and incident response efforts.

Benefits of Network Detection & Response

Stay ahead of cyber criminals

Attackers now have widespread access to what were previously nation-state level tools designed to evade specific security tools. NDR solutions provide an extra layer of security against both sophisticated network attacks and highly organized threat actors.

Move beyond logs and endpoint security

SIEMs have blind spots, and endpoints detection capabilities can be evaded or disabled by a determined adversary. Both SIEM and endpoint tools struggle with detecting adversaries that are not specifically malware-based, such as lateral movement using stolen credentials.

Get fewer alerts

With NDR systems, after a threat is detected, rules are applied to the analytic result to contextualize knowledge of an organization and its threat landscape. This approach further adjusts the initial risk score of an alert by determining whether the alert is indeed a high priority or if the alert can be downgraded in severity based on contextual enrichment.

The truth is in the traffic

Network traffic is massive and pervasive. The sheer amount of network metadata, protocol logs, and network artifacts makes it extremely difficult, if not nearly impossible, for an adversary to hide their activities across or disable an entire network.

Protect your IoT devices

Many IoT devices are either too tiny (like your internet-connected thermostat), too many to manage at scale (think every device that has an IP address), or simply too old (in case of manufacturing systems) and simply do not have the ability to run endpoint security software or analytics. NDR enables organisations to protect these devices by analyzing their network activity without the overhead of having to manage individual device software.

Bolster your overall defense

High-maturity clients use NDR and other network-based technologies as one of the layers in their SOCs, alongside endpoint-, log- and cloud-based technologies for threat visibility.

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Frequently Asked Questions

Network detection and response (NDR) solutions use a combination of non-signature-based advanced analytical techniques such as machine learning to detect suspicious network activity. This enables teams to respond to anomalous or malicious traffic and threats that other security tools miss.

NDR solutions continuously monitor and analyse raw enterprise network traffic to generate a baseline of normal network behavior. When suspicious network traffic patterns that deviate from this baseline are detected, NDR tools alert security teams to the potential presence of threats within their environment.

Networks are extending into the cloud and continuously growing in both size and complexity. This has led to an unprecedented volume of data traversing the distributed network and created a perfect environment for malicious actors to hide in. NDR solutions solve this problem by collecting telemetry from network devices and applying analytical techniques like machine learning to detect threats that other tools miss.

NDR solutions and tools can:

  • Detect anomalous network traffic that traditional tools miss by applying non-signature-based detection techniques such as behavioral analytics and machine learning.
  • Model a baseline of what normal network behavior looks like and alert security teams on any suspicious traffic that falls outside of that normal range.
  • Monitor all traffic flows—whether entering and exiting the network or moving within the network—so that teams have the extended visibility needed to identify and mitigate security incidents, regardless of where a threat originates.
  • Analyse raw network telemetry in real-time or near real time and provide timely alerts to allow teams to improve incident response times.
  • Attribute a malicious behavior to a specific IP address and perform forensic analyses to determine how threats have moved laterally within an environment. This allows teams to see what other devices might be infected, leading to faster incident response and threat containment, and better protection against unfavorable business impacts.
  • Provide response capabilities that can enhance manual incident response and threat hunting efforts or streamline operations and save teams time through automation.

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