Splunk Security
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The analytic detects the creation of cloud compute instances using previously unseen image IDs. It leverages cloud infrastructure logs to identify new image IDs that have not been observed before. This activity is significant because it may indicate unauthorized or suspicious activity, such as the deployment of malicious payloads or unauthorized access to sensitive information. If confirmed malicious, this could lead to data breaches, unauthorized access, or further compromise of the cloud environment. Immediate investigation is required to determine the legitimacy of the instance creation and to mitigate potential threats.
This rule detects unusually high video latency in Zoom sessions. Elevated latency, particularly above 300ms, can be an indicator of suspicious activity such as Remote Employment Fraud (REF), where threat actors might be operating from geographically distant locations or using compromised network infrastructure, leading to poor connection quality. The rule extracts and analyzes average and overall video latency from Zoom Quality of Service (QoS) logs for participants.
This rule detects rare input devices (microphones) used during Zoom meetings. It specifically looks for microphone devices that are not commonly observed, while excluding typical devices like iPhones, FaceTimes, AirPods, and MacBooks. The primary goal is to identify unusual device usage that could be indicative of Remote Employment Fraud (REF), where actors might use non-standard equipment. This is a hunting query designed to flag anomalies for further investigation.
The following analytic detects the suspicious sysmon service stop. This behavior is critical for a SOC to monitor because it may indicate attempts to gain unauthorized access or maintain control over a system. Such actions could be signs of malicious activity. If confirmed, this could lead to serious consequences, including a compromised system, unauthorized access to sensitive data, or even a wider breach affecting the entire network. Detecting and responding to these signs early is essential to prevent potential security incidents.
The analytic detects suspicious access or modification of the sshd_config file on Linux systems. It leverages data from Linux Auditd, focusing on command-line executions involving processes like "cat," "nano," "vim," and "vi" accessing the sshd_config file. This activity is significant because unauthorized changes to sshd_config can allow threat actors to redirect port connections or use unauthorized keys, potentially compromising the system. If confirmed malicious, this could lead to unauthorized access, privilege escalation, or persistent backdoor access, posing a severe security risk.
The following analytic detects potential tampering with cronjob files on a Linux system by identifying 'echo' commands that append code to existing cronjob files. It leverages logs from Linux Auditd, focusing on process names, parent processes, and command-line executions. This activity is significant because adversaries often use it for persistence or privilege escalation. If confirmed malicious, this could allow attackers to execute unauthorized code automatically, leading to system compromises and unauthorized data access, thereby impacting business operations and data integrity.
The analytic detects modifications to the Windows RunMRU registry key, which stores a history of commands executed through the Run dialog box (Windows+R). It leverages Endpoint Detection and Response (EDR) telemetry to monitor registry events targeting this key. This activity is significant as malware often uses the Run dialog to execute malicious commands while attempting to appear legitimate. If confirmed malicious, this could indicate an attacker using indirect command execution techniques for defense evasion or persistence. The detection excludes MRUList value changes to focus on actual command entries.
The following analytic detects the creation of the doas.conf file on a Linux host. This file is used by the doas utility to allow standard users to perform tasks as root, similar to sudo. The detection leverages Linux Auditd data, focusing on the creation of the doas.conf file. This activity is significant because it can indicate an attempt to gain elevated privileges, potentially by an adversary. If confirmed malicious, this could allow an attacker to execute commands with root commands with root privileges, leading to full system compromise.
This analytic detects the suspicious disable or modification of system firewalls on Linux systems. Specifically, it looks for `SERVICE_STOP` events for `firewalld` or `ufw` units. This behavior is critical to monitor as it may indicate attempts to gain unauthorized access or maintain control over a system by bypassing network controls. Such actions could be signs of malicious activity, potentially leading to a compromised system, unauthorized access to sensitive data, or a wider network breach. Early detection and response are essential to prevent potential security incidents.
The analytic detects suspicious stopping of the `osquery` service, which may indicate an attempt to disable monitoring and evade detection. `Osquery` is a powerful tool used for querying system information and detecting anomalies, and stopping its service can be a sign that an attacker is trying to disrupt security monitoring or hide malicious activities. By monitoring for unusual or unauthorized stops of the `osquery` service, this analytic helps identify potential efforts to bypass security controls, enabling security teams to investigate and respond to possible threats effectively.
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