Lateral movement detection and prevention. The buck stops here.
Lateral movement detection is a cybersecurity concept that involves identifying the techniques attackers use to move through a network in search of targeted data or system vulnerabilities. After gaining initial access to a network, attackers often move laterally—i.e., from one system to another—with the aim of escalating their privileges, often by stealing credentials, to gain access to more valuable resources. They might also deploy tools, create backdoors, or establish a foothold for persistence.
In the context of cybersecurity, lateral movement is a critical stage of an attack, as it allows the attacker to establish a stronger foothold in an environment and potentially reach high-value targets. This could include sensitive databases, personal information, financial data, intellectual property, credentials, or critical infrastructure controls. What an attacker chooses to target can depend on their motivations, which can range from financial gain to corporate espionage, political motivations, or simply causing disruption. Controlling lateral movement is, therefore, a critical part of cyber defense there to stop these bad actors in their tracks.
According to Security Magazine, in 2023, there are over 2,200 cyberattacks each day (800,000 attacks each year). That’s nearly 1 cyberattack every 39 seconds. With numbers like that, there’s every likelihood they’ll get in eventually – but if they do, they shouldn’t be allowed to get any further.
Cyber attackers employ a variety of tactics to move laterally within a network after they’ve gained initial access. These can include:
- Credential Harvesting: Cyber attackers commonly steal user credentials through tactics such as phishing, where they trick users into voluntarily providing their login details via deceptive emails or fake websites. They may also use keyloggers to record keystrokes, malware to harvest stored credentials, or exploit system vulnerabilities to capture login data.
- Exploiting Vulnerabilities: If software or systems within the network have unpatched vulnerabilities, attackers can exploit these to gain access and move laterally.
- Pass-the-Hash (PtH): In this attack, the threat actor steals hashed user credentials (a form of encrypted password) from a compromised system, then uses those hashes to authenticate to other systems on the network. This allows the attacker to move laterally across the network, bypassing the need to crack or know the actual plaintext password.
- Living off the Land (LotL): Attackers can use native system tools and processes to move within a network, which can be particularly challenging to detect and prevent because they use tools and software intended for legitimate purposes. They also leave fewer traces compared to other types of attacks, as they don’t rely on deploying new, potentially detectable malware.
- Remote Desktop Protocol (RDP): Cybercriminals can exploit vulnerabilities in the RDP, a network communications protocol developed by Microsoft. They may gain unauthorized access by cracking weak user passwords, employing stolen credentials, or exploiting unpatched software vulnerabilities. Once in, they can remotely control the system as if they were sitting in front of it.
- Lateral Movement Tools: Various frameworks, some of which originally developed as legitimate tools for system administration, penetration testing, and security research, have been developed specifically to aid in lateral movement, including popular frameworks like PowerShell Empire, Mimikatz, and Metasploit.
Understanding these tactics is key to developing effective lateral movement protection strategies. The goal is to minimize the opportunities for lateral movement by maintaining good cyber hygiene practices, such as regular patching, strong access controls, network segmentation, and continuous network monitoring.
Lateral movement detection is protection step one
Lateral movement detection involves deploying security measures to identify and alert to this kind of activity as quickly as possible. This includes monitoring for unusual or unexpected system interactions, suspicious user behavior, and inconsistencies in network traffic patterns. For best practices, this includes baselining regular and acceptable activity within an environment – be it users, applications, or even devices – and measuring against that baseline for variation and deviation in the future.
If you don’t know what your assets are, you can’t protect them.
There is often a security visibility gap, especially in production applications, which poses a security challenge. Comprehending the attack surface, through the detection and discovery process, means uncovering applications and resources. A significant number of organizations lack knowledge, however, regarding the utilization of servers and other workloads across their data center and cloud environments. This is where automated lateral movement detection tools come in, by creating a baseline of acceptable. This typically involves monitoring and analyzing network and system behavior over a certain period of time during normal operations. This process helps in understanding typical user behavior, normal system performance, and regular network traffic patterns. Machine learning algorithms can be used to learn from this data and establish what’s “normal” for that specific environment.
Once this baseline is established, the lateral movement detection system can then see any deviations from the norm, which might indicate potential security threats. For instance, if a user suddenly starts downloading large volumes of data or a system starts making unusual network connections, these could be flagged as suspicious activities.
Responding to lateral movement detection
The overall discipline of lateral movement protection is a critical component of a robust cybersecurity defense, helping to contain potential breaches, prevent escalation of access, and mitigate the impact of both external and internal threats.
Lateral movement protection is crucial for several reasons:
- Early Threat Detection: Detecting lateral movement can lead to early identification of a breach, allowing organizations to respond swiftly and limit damage. It’s a proactive approach to threat detection that doesn’t just wait for the final attack on valuable resources.
- Containment of Breaches: If a breach does occur, lateral movement protection helps contain the attack, preventing it from spreading across the network. This often means employing the benefits of network segmentation, zero trust best practices, and microsegmentation, to significantly reduce the overall impact of any attack.
- Preventing Escalation: By blocking lateral movement, organizations can prevent attackers from escalating their privileges or access within the network. This stops attackers from gaining control over critical systems or stealing sensitive information.
- Regulatory Compliance: Many industry regulations and standards require organizations to demonstrate that they have controls in place to detect and prevent lateral movement. Effective lateral movement protection can help meet these compliance requirements.
- Mitigating Advanced Threats: Sophisticated cyber threats, like Advanced Persistent Threats (APTs), often rely on lateral movement to achieve their objectives. By focusing on lateral movement protection, organizations can better defend against these advanced threats.
Remember, it’s not just external threats that lateral movement protection helps mitigate. Insider threats, whether malicious or accidental, can also lead to security incidents that involve lateral movement within the network. Security teams must possess the capability to discover, understand, and enforce application and workload behaviors, thereby establishing a perpetually trustworthy environment.
It is important to be able to:
- Comprehend the Attack Surface: Traditional network security solutions often fall short in detecting and preventing lateral movement by external threats or compromised insiders.
- Uncover Applications and Resources: Many organizations lack complete visibility into the usage of servers and other workloads across their data center and cloud environments. Application behavioral mapping is often overlooked, but a critical part of lateral movement detection and prevention – it is often said that the largest security gap is in the application environment.
- Recognize Overly Broad Entitlements: User and machine entitlements often carry excessive privileges that are seldom reviewed or revoked. This can heighten the risk of privileged access and movement across the infrastructure if compromised.
- Maintaining Peak Operations: Balancing security with performance can be challenging. Specifically, mitigating high-risk activities across workloads without impacting application performance presents a significant obstacle.
By implementing lateral movement protection, organizations can strengthen their overall security posture against a wide range of threats, respond to security incidents more effectively, stop attacks in their tracks before they lead to data breaches or system damage. The ultimate goal is to minimize the potential impact of an attack by limiting the attacker’s ability to move freely within the network.
Zero trust for lateral movement security
Zero Trust is a security model premised on the principle of “never trust, always verify,” requiring validation of all requests for network access, regardless of origin, enforcing least-privilege access, and necessitating continuous monitoring and adaptation to potential security risks.
Under a zero-trust framework, continuous vigilance and analysis of network and system activities for anomalous behavior are imperative, and this plays an active role in lateral movement detection and prevention.
This can be facilitated by leveraging security tools such as intrusion detection and prevention systems, firewalls, and other security technologies. Having clear visibility is crucial in comprehending the access dynamics of applications and accounts. Intrusion detection and prevention systems serve to identify and halt potential cyber threats by scrutinizing network traffic for any unusual activity. Firewalls fortify networks against unauthorized access by managing inbound and outbound traffic according to established security guidelines. Any activity deviating from the norm – as determined by lateral movement detection baselining of activity – should be marked for immediate examination.