Lateral movement is a sophisticated technique employed by cybercriminals to navigate through a network after initially compromising an endpoint. Once inside, attackers use stolen credentials or exploit vulnerabilities to access additional devices, applications, and data. By disguising their actions as legitimate network traffic, they can remain undetected, extending the duration and impact of their attack.

How lateral movement occurs

Lateral movement typically begins when a threat actor breaches an endpoint connected to a network lacking stringent access controls. They might exploit software vulnerabilities, leverage malware, or use social engineering tactics to gain initial access. Traditional security measures often fail to detect these intrusions because the malicious activity mimics normal user behavior.

The stages of lateral movement

Lateral movement can be broken down into three primary stages:

Network exploration: Attackers map out the network to understand its structure, identifying vulnerable points, open firewall ports, and other weaknesses. This information helps them plan their next steps.

System compromise: Using methods such as credential dumping and privilege escalation, attackers gain access to various parts of the system. Phishing attacks are common in this stage to obtain login credentials.

Objective execution: Once the attackers find their target, they execute their primary objective, which could include deploying malware, stealing data, or disrupting services

Common lateral movement techniques

Lateral movement isn't a single method but a collection of tactics tailored to the attacker’s goals. Some prevalent techniques include:

Pass the Hash (PtH): Attackers use stolen password hashes for authentication, bypassing the need for plain text passwords.

Pass the Ticket (PtT): Exploiting the Kerberos authentication protocol, attackers use stolen tickets to gain access without knowing the password.

Remote service exploitation: Attackers exploit vulnerabilities in remote services to move across the network.

Internal spear phishing: Compromised accounts are used to phish for additional credentials from within the network.

SSH hijacking: Attackers intercept SSH connections to gain access to other systems.

Windows admin shares: Administrative access enables attackers to use default admin shares for lateral movement.

Security challenges of lateral movement

Networks that allow unrestricted lateral movement are particularly vulnerable, as attackers can quickly spread across hosts. The rise of hybrid and remote work environments exacerbates this issue, introducing varied endpoints with different security postures, each a potential entry point for attackers.

Advanced Persistent Threats (APTs) pose a significant challenge, as skilled attackers can remain undetected for extended periods, exfiltrating data and compromising critical systems.

Strategies to prevent and detect lateral movement

Prevention Techniques

Robust endpoint security: Implementing comprehensive endpoint protection can prevent initial breaches. This includes endpoint detection and response (EDR) solutions that provide continuous monitoring and threat detection.

Protect high-value targets: Accounts with administrative privileges should be heavily protected with stringent security measures, such as multi-factor authentication (MFA).

Microsegmentation: Creating secure zones within the network can isolate workloads and limit the spread of an attack.

Zero Trust approach: Adopt a security framework where no one is trusted by default. This involves strict access controls and continuous verification of all devices and users.

Detection Techniques

Monitoring authentication activity: Regularly reviewing authentication logs can help identify suspicious activities indicative of credential theft.

User behavior analysis: Machine learning can establish a baseline of normal behavior and detect anomalies that may suggest an attack.

Deception strategies: Deploying decoy assets can lure attackers and trigger alerts when interacted with.

Proactive threat search: Actively searching for threats within the network can help identify and mitigate attacks early.

Leveraging Zero Trust to mitigate lateral movement

Zero Trust is a security model that assumes no entity—internal or external—can be trusted by default. It enforces strict access controls and continuously verifies every user and device. Here’s how Zero Trust can help mitigate lateral movement:

Contextual access policies: Access is granted based on multiple factors, such as user identity, device health, and location.

Microsegmentation: Network resources are segmented at a granular level, reducing the attack surface.

Continuous monitoring and verification: All interactions within the network are monitored, and access is regularly reassessed to detect and block malicious activities.

Strong MFA: Implementing MFA adds an extra layer of security, making it harder for attackers to use stolen credentials.

Implementing Zero Trust with NVIS AI

NVIS AI’s Zero Trust solution embodies these principles, offering robust protection against lateral movement. By implementing granular microsegmentation, NVIS AI ensures that every user has permissions to only the assets they are granted.

NVIS AI’s Zero Trust solution is distinguished by several key features:

NVIS overlay: Conceals public IP addresses to prevent them from being blocked, sniffed, or traced.

Layer 2 encryption: Establishes direct, encrypted peer-to-peer connections at Layer 2, obscuring the source, destination, and traffic between endpoints.

AI-Driven provisioning: Automates complex network configurations for quick and secure federated networks across diverse environments, including on-premises, cloud, multi-cloud, IoT, and OT.

Conclusion

In an era where cyber threats are increasingly sophisticated, lateral movement remains a significant challenge. However, with the right strategies and technologies, it is possible to prevent and detect these attacks effectively.

Adopting a Zero Trust approach and leveraging advanced tools like NVIS AI’s solutions can help businesses safeguard their networks and protect sensitive data from malicious actors. By staying vigilant and proactive, organizations can minimize the risk of lateral movement and ensure robust cybersecurity defenses.

Contact our team to learn how NVIS AI's ZTNA solution can enhance your organization's security. Feel free to also schedule a demo or talk with our team to demonstrate how NVIS AI secures access to your network.