Active Directory Lateral Movement Identified via Splunk Correlation

This analytic identifies potential lateral movement activities within an organization’s Active Directory (AD) environment. It operates by correlating multiple analytics from the “Active Directory Lateral Movement” analytic story within a specified timeframe. This is a significant concern for security operations centers (SOCs) because lateral movement is a tactic frequently used by attackers to expand their access within a network. If confirmed as malicious, such activity can enable attackers to escalate privileges, access sensitive information, and establish persistence within the environment, potentially resulting in severe security breaches. The correlation relies on risk scoring and the frequency of related events to highlight suspicious behavior.

Attack Chain

1. Initial compromise of a single endpoint within the Active Directory environment through phishing or exploitation of a public-facing application.
2. Execution of reconnaissance commands to enumerate users, groups, and systems within the Active Directory domain using tools like net.exe or PowerView.
3. Discovery of privileged accounts or systems with sensitive data by querying Active Directory.
4. Attempted credential dumping using tools like Mimikatz to obtain valid credentials for lateral movement.
5. Leveraging obtained credentials to authenticate to other systems within the environment using protocols like SMB or RDP.
6. Execution of malicious code on the remotely accessed systems, such as malware deployment or data exfiltration.
7. Establishing persistence on the compromised systems to maintain access and continue lateral movement.

Impact

A successful lateral movement campaign within Active Directory can lead to widespread compromise of the environment. Attackers can gain access to sensitive data, escalate privileges to domain administrator, and deploy ransomware across the network. The damage can include data theft, financial loss, and disruption of critical business operations. Given that this detection requires four correlated events to trigger, a successful attack could involve the compromise of multiple systems, thus greatly amplifying the potential impact.

Recommendation

• Tune the source_count threshold in the SPL search based on your environment’s baseline activity to reduce false positives. The default value of 4 might be too low for larger environments.
• Investigate correlated risk events flagged by this search to confirm or refute lateral movement. Use the drilldown searches provided to view detection results and risk events associated with the identified risk object.
• Review and adjust the risk scoring of individual analytics within the “Active Directory Lateral Movement” analytic story to ensure accurate prioritization of alerts.
• Consider implementing additional filtering based on risk score values to reduce false positives and focus on the most critical events.
• Enable endpoint detection and response (EDR) solutions to provide greater visibility into endpoint activity and facilitate rapid response to lateral movement attempts.