Stopping Lateral Movement: How NDR Identifies Stealthy Attackers in Your Network

Lateral movement is a key tactic used by cyber attackers to expand their foothold within a network after an initial compromise. Once inside, adversaries stealthily navigate through systems, escalate privileges, and exfiltrate sensitive data—all while evading traditional security measures. Network Detection and Response (NDR) solutions play a critical role in identifying and stopping these stealthy attackers before they can cause significant damage.

Understanding Lateral Movement

Lateral movement refers to the techniques attackers use to pivot from one compromised system to another within a network. This movement allows them to explore network resources, gain higher privileges, and reach their ultimate target—whether that’s sensitive data, critical applications, or operational infrastructure.

Some common lateral movement techniques include:

• Credential Theft and Abuse: Attackers steal legitimate credentials to access other systems.

• Remote Execution Tools: Using tools like PsExec, PowerShell, or RDP to move between endpoints.

• Exploiting Vulnerabilities: Taking advantage of unpatched software to gain further access.

• Living-off-the-Land (LotL) Attacks: Leveraging built-in administrative tools to blend in with normal activity.

How NDR Detects and Stops Lateral Movement

Unlike traditional security tools that rely on static rules and signatures, NDR solutions leverage AI, machine learning, and behavioral analytics to detect anomalous activity in real time. Here’s how NDR helps identify and mitigate lateral movement:

1. Continuous Network Monitoring

NDR solutions monitor east-west traffic within the network, which is often overlooked by perimeter defenses like firewalls and endpoint protection. By analyzing this internal traffic, NDR can identify unusual patterns that indicate lateral movement attempts.

2. Behavioral Analytics and Anomaly Detection

Rather than relying solely on predefined threat signatures, NDR establishes a baseline of normal network behavior. When deviations occur—such as unexpected access requests, unusual remote executions, or unauthorized credential usage—the system triggers alerts for further investigation.

3. Detecting Unusual Authentication Patterns

Attackers frequently use compromised credentials to access multiple systems. NDR detects unusual authentication behaviors, such as:

• Logins from unexpected locations or devices.

• High-frequency authentication attempts.

• Accounts accessing sensitive systems they normally don’t interact with.

4. Identifying Lateral Movement Tools and Techniques

NDR solutions analyze traffic for known indicators of compromise (IoCs) related to lateral movement tools like:

• Mimikatz (for credential dumping)

• PsExec, WMI, and RDP (for remote execution)

• SMB and DCOM traffic anomalies (signs of unauthorized system access)

5. Automated Threat Response and Containment

When suspicious activity is detected, NDR solutions can automate response actions, such as:

• Isolating compromised endpoints to prevent further movement.

• Alerting security teams with contextual insights to speed up investigations.

• Integrating with other security tools (SIEM, SOAR, XDR) for coordinated threat mitigation.

Enhancing Cyber Resilience with NDR

By proactively detecting stealthy attackers and stopping lateral movement, NDR strengthens an organization’s cybersecurity posture. When combined with other security layers, such as Extended Detection and Response (XDR) and Cloud-Native Application Protection Platforms (CNAPP), NDR ensures a comprehensive defense against modern threats.

Key Takeaways

• Lateral movement is a critical attack phase that allows adversaries to escalate privileges and access sensitive data.

• Traditional security tools often miss lateral movement because they focus on perimeter defenses.

• NDR continuously monitors internal network traffic, detects anomalies, and automatically responds to threats.

• Organizations that implement NDR gain better visibility, faster threat detection, and enhanced resilience against cyber threats.