Correlation detection rules

The following analytic identifies potential threats related to the theft or forgery of authentication certificates. It detects when five or more analytics from the Windows Certificate Services story trigger within a specified timeframe. This detection leverages aggregated risk scores and event counts from the Risk data model. This activity is significant as it may indicate an ongoing attack aimed at compromising authentication mechanisms.

The following analytic identifies potential exploitation of Windows Exchange servers via ProxyShell or ProxyNotShell vulnerabilities, followed by post-exploitation activities such as running nltest, Cobalt Strike, Mimikatz, and adding new users. It leverages data from multiple analytic stories, requiring at least five distinct sources to trigger, thus reducing noise.

This analytic detects a correlation between privileged account creation on Cisco IOS devices and subsequent inbound SSH connections to non-standard ports or sshd_operns by correlating risk events This correlation identifies when both "Cisco IOS Suspicious Privileged Account Creation" and SSH-related Snort detections ("SSH Connection to sshd_operns" or "SSH Connection to Non-Standard Port") fire for the same network device.

This analytic correlates risk events between privileged account creation on Cisco IOS devices and HTTP requests to privileged execution paths such as `/level/15/exec/-/*`. APT actors have been observed creating privileged accounts and then running commands on routers via HTTP GET or POST requests that target privileged execution paths. These requests allow attackers to execute commands with the highest privilege level (15) on Cisco devices without requiring interactive SSH access.

The following analytic identifies four or more distinct post-exploitation behaviors on a Windows system. It leverages data from the Risk data model in Splunk Enterprise Security, focusing on multiple risk events and their associated MITRE ATT&CK tactics and techniques. This activity is significant as it indicates potential malicious actions following an initial compromise, such as persistence, privilege escalation, or data exfiltration.

The following analytic identifies instances where three or more distinct registry modification events associated with MITRE ATT&CK Technique T1112 are detected. It leverages data from the Risk data model in Splunk, focusing on registry-related sources and MITRE technique annotations. This activity is significant because multiple registry modifications can indicate an attempt to persist, hide malicious configurations, or erase forensic evidence.

The following analytic identifies instances where four or more distinct detection analytics are associated with malicious command line behavior on a specific host. This detection leverages the Command Line Interface (CLI) data from various sources to identify suspicious activities. This behavior is significant as it often indicates attempts to execute malicious commands, access sensitive data, install backdoors, or perform other nefarious actions.

The following analytic identifies potential exploitation of Log4Shell CVE-2021-44228 by correlating multiple MITRE ATT&CK tactics detected in risk events. It leverages Splunk's risk data model to calculate the distinct count of MITRE ATT&CK tactics from Log4Shell-related detections. This activity is significant because it indicates a high probability of exploitation if two or more distinct tactics are observed.

The following correlation identifies multiple risk events associated with the "Living Off The Land" analytic story, indicating potentially suspicious behavior. It leverages the Risk data model to aggregate and correlate events tagged under this story, focusing on systems with a high count of distinct sources. This activity is significant as it often involves the use of legitimate tools for malicious purposes, making detection challenging.

The following analytic identifies potential Linux persistence and privilege escalation activities. It leverages risk scores and event counts from various Linux-related data sources, focusing on tactics associated with persistence and privilege escalation. This activity is significant for a SOC because it highlights behaviors that could allow an attacker to maintain access or gain elevated privileges on a Linux system.

The following analytic identifies potential privilege escalation activities within an organization's Active Directory (AD) environment. It detects this activity by correlating multiple analytics from the Active Directory Privilege Escalation analytic story within a specified time frame. This is significant for a SOC as it helps identify coordinated attempts to gain elevated privileges, which could indicate a serious security threat.

The following analytic identifies potential lateral movement activities within an organization's Active Directory (AD) environment. It detects this activity by correlating multiple analytics from the Active Directory Lateral Movement analytic story within a specified time frame. This is significant for a SOC as lateral movement is a common tactic used by attackers to expand their access within a network, posing a substantial risk.

The following analytic identifies high-risk activities within repositories by correlating repository data with risk scores. It leverages findings and intermediate findings created by detections from the Dev Sec Ops analytic stories, summing risk scores and capturing source and user information. The detection focuses on high-risk scores above 100 and sources with more than three occurrences.

The following analytic identifies potential AWS S3 exfiltration behavior by correlating multiple risk events related to Collection and Exfiltration techniques. It leverages risk events from AWS sources, focusing on instances where two or more unique analytics and distinct MITRE ATT&CK IDs are triggered for a specific risk object. This activity is significant as it may indicate an ongoing data exfiltration attempt, which is critical for security teams to monitor.

The following correlation identifies when a user exceeds a risk threshold based on multiple suspicious Okta activities. It leverages the Risk Framework from Enterprise Security, aggregating risk events from "Suspicious Okta Activity," "Okta Account Takeover," and "Okta MFA Exhaustion" analytic stories. This detection is significant as it highlights potentially compromised user accounts exhibiting multiple tactics, techniques, and procedures (TTPs) within a 24-hour period.