Windows Post Exploitation Risk Behavior Detection

This detection identifies potential malicious actions on a Windows system after an initial compromise. It uses data from the Risk data model in Splunk Enterprise Security to correlate multiple risk events and their associated MITRE ATT&CK tactics and techniques. The analytic focuses on identifying a combination of post-exploitation behaviors, such as credential access, discovery, and privilege escalation. A high number of distinct post-exploitation behaviors occurring on a single host suggests that an attacker may be attempting to maintain control, escalate privileges, or exfiltrate data. This can lead to significant security breaches and data loss if not detected and addressed promptly. The original detection was released in June 2023 and last modified in May 2026.

Attack Chain

1. Initial compromise occurs through an unspecified method (e.g., phishing, exploit of a public-facing application).
2. Attacker gains initial access to the compromised Windows system.
3. Attacker performs system discovery (T1016) to gather information about the environment.
4. Attacker attempts to access credentials (T1003, T1552) stored on the system.
5. Attacker performs account discovery (T1082) to identify user accounts.
6. Attacker attempts privilege escalation (T1069) to gain higher-level access.
7. Attacker uses OS Credential Dumping (T1003) to retreive credentials.
8. The attacker moves laterally to other systems, or exfiltrates sensitive data.

Impact

A successful post-exploitation attack can lead to a variety of negative outcomes, including data breaches, system downtime, and financial losses. Attackers can use compromised systems to steal sensitive information, disrupt business operations, and launch further attacks against other organizations. Identifying post-exploitation behaviors early can significantly reduce the impact of an attack.

Recommendation

• Deploy this analytic to your Splunk Enterprise Security instance to identify potential post-exploitation activity.
• Modify the source_count value in the search query based on your environment to reduce false positives, as described in the “How To Implement” section.
• Investigate and tune any anomaly analytics to lower or increase risk based on organization importance, as mentioned in the “How To Implement” section.
• Use the drilldown searches provided to view detection results and risk events associated with specific risk objects.
• Review the MITRE ATT&CK techniques associated with this detection (T1012, T1049, T1069, T1016, T1003, T1082, T1115, T1552) to understand potential attacker behaviors.
• Consult the provided reference URL for more information on post-exploitation techniques, specifically winPEASbat which can be used to discover privilege escalation paths.