Cyberattacks rarely end once an attacker gains access to a network. Instead, attackers typically attempt to expand their control by moving from one system to another within the organization. This process, known as lateral movement, allows attackers to locate valuable data, escalate privileges, and compromise additional devices. Detecting lateral movement quickly is essential to limiting damage during a cyber incident. One of the most effective technologies for identifying such behavior is Network Detection and Response (NDR).
Network Detection and Response solutions monitor and analyze network traffic to identify suspicious or malicious activities. Unlike traditional security tools that focus mainly on perimeter protection, NDR provides visibility into internal network communications, also known as east–west traffic. By analyzing how devices interact with each other, NDR helps security teams detect abnormal patterns that may indicate an attacker moving through the network.
One of the primary strengths of NDR is its ability to use behavioral analytics. NDR systems continuously observe network activity and establish a baseline of what is considered normal behavior for users, devices, and applications. When the system detects behavior that deviates from this baseline—such as a device communicating with multiple servers it normally does not access—it generates an alert. These anomalies often signal potential lateral movement or other malicious activities.
Attackers frequently rely on legitimate network protocols to move between systems because doing so helps them avoid detection. Common protocols used for lateral movement include Remote Desktop Protocol (RDP), Server Message Block (SMB), and Secure Shell (SSH). NDR tools inspect these protocols and analyze session patterns, login attempts, and data transfers. If an unusual pattern appears, such as repeated login failures or a sudden spike in internal remote connections, the system flags it for investigation.
Another important capability of NDR is the detection of credential abuse. Many attackers gain access to privileged accounts by stealing or cracking passwords. Once they obtain these credentials, they use them to access additional systems across the network. NDR can detect suspicious authentication activities, such as a user logging in from multiple devices simultaneously or accessing resources outside their typical scope. These behaviors often indicate compromised credentials being used for lateral movement.
NDR is also effective at identifying internal reconnaissance, which is a common step before lateral movement. Attackers may scan the network to identify vulnerable devices, open ports, or valuable servers. NDR solutions can recognize unusual scanning activity or probing behavior originating from internal machines. Since legitimate users rarely perform such scans, these actions are strong indicators of malicious intent.
Another benefit of NDR is its ability to provide real-time threat detection and response. When suspicious behavior is detected, the system can alert security teams immediately. Some advanced NDR platforms can also integrate with other security tools such as Security Information and Event Management (SIEM) systems and Endpoint Detection and Response (EDR) solutions. This integration allows organizations to correlate network events with endpoint activity, providing a more complete view of the attack.
Implementing NDR in an organization requires careful planning. Sensors should be placed in strategic network locations to capture both inbound and internal traffic. Security teams must also configure alert thresholds carefully to reduce false positives while still detecting genuine threats. Regular updates and tuning of detection models ensure that the system remains effective against evolving attack techniques.
In conclusion, lateral movement is a critical stage in many cyberattacks, enabling attackers to spread throughout a network and reach sensitive resources. Network Detection and Response provides organizations with deep visibility into internal network activity and helps detect suspicious behavior that may indicate an ongoing attack. By leveraging behavioral analytics, protocol inspection, and anomaly detection, NDR significantly improves an organization’s ability to identify and stop lateral movement before it leads to serious damage.
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