Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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The following analytic detects the suspicious auditd 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 cloud API calls executed by user roles that have not previously run these commands. It leverages the Change data model in Splunk to identify commands executed by users with the user_type of AssumedRole and a status of success. This activity is significant because new commands from different user roles can indicate potential malicious activity or unauthorized actions. If confirmed malicious, this behavior could lead to unauthorized access, data breaches, or other damaging outcomes by exploiting new or unmonitored commands within the cloud environment.
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.
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 the loading of known vulnerable Windows drivers, which may indicate potential persistence or privilege escalation attempts. It leverages Sysmon EventCode 6 to identify driver loading events and cross-references them with a list of vulnerable drivers. This activity is significant as attackers often exploit vulnerable drivers to gain elevated privileges or maintain persistence on a system. If confirmed malicious, this could allow attackers to execute arbitrary code with high privileges, leading to further system compromise and potential data exfiltration.
The following analytic detects suspicious modifications to the registry that may indicate a UAC (User Account Control) bypass attempt via the SilentCleanup task. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on registry changes in the path "*\Environment\windir" with executable values. This activity is significant as it can allow an attacker to gain high-privilege execution without user consent, bypassing UAC protections. If confirmed malicious, this could lead to unauthorized administrative access, enabling further system compromise and persistence.
The analytic detects changes to the PowerShell ExecutionPolicy in the registry to "Unrestricted" or "Bypass." This activity is significant because setting the ExecutionPolicy to these values can allow the execution of potentially malicious scripts without restriction. If confirmed malicious, this could enable an attacker to execute arbitrary code, leading to further compromise of the system and potential escalation of privileges.
This rule detects the execution or creation of files identified as Remote Access Tools (RATs) based on a Google Cloud Threat Intelligence (GCTI) feed. It correlates process launch, module load, or file creation events with known SHA256 hashes of RATs provided by the GCTI feed. The rule specifically looks for events where the SHA256 hash of the process or file matches a hash from the 'Remote Access Tools' threat feed within the GCTI graph.
This rule detects when a file, identified as malicious by Google Safe Browsing, initiates an outbound network connection to an IP address known to be a Tor Exit Node, as identified by Google Cloud Threat Intelligence (GCTI) Feed. This indicates potential command and control (C2) communication or data exfiltration by malware attempting to anonymize its network traffic.
This rule detects outbound network connections to IP addresses that have been observed for the first time within the last 24 hours. It specifically excludes connections to private IP address ranges (RFC1918). The detection relies on correlating current network connection events with historical 'first seen' data for IP addresses from an entity graph.
This rule detects when a user, identified as having a high-risk relationship with GCP resources (specifically those containing sensitive data like US Social Security Numbers via GCP DLP context), downloads an executable file. The detection correlates network proxy events showing executable downloads or large file transfers with EDR events indicating Microsoft Excel activity on the same host and by the same user within a 5-minute window. This scenario is indicative of a potential malicious macro in an Excel document downloading and executing malware.
This rule detects outbound network connections to IP addresses that exhibit low prevalence within the monitored environment. Specifically, it flags connections to IPs that have a rolling maximum prevalence of 1 to 3 occurrences over a 10-day period. This behavior can be indicative of command and control (C2) communication, data exfiltration, or other suspicious activities where adversaries might use newly registered or rarely seen infrastructure.
This rule detects outbound network connections to known Tor exit nodes. It leverages a Google Cloud Threat Intelligence (GCTI) feed that provides a list of current Tor exit node IP addresses. The rule specifically looks for allowed network connections where the target IP address is identified as a Tor exit node by the GCTI feed. This can indicate an attempt to anonymize network traffic, which is often associated with malicious activity.
This rule identifies process creations or file creations where the associated file has been tagged as an 'exploit' by VirusTotal. It leverages enrichment from a VirusTotal integration to flag potentially malicious activity related to exploit execution.
This rule detects when a known 'benign' binary, as identified by the Google Cloud Threat Intelligence (GCTI) Feed, initiates an outbound network connection to an IP address identified as a Tor exit node, also from the GCTI Feed. The rule also increases the risk score if the Tor exit node is located in specific high-risk countries (Cuba, Iran, North Korea, Russia, Syria). This indicates potential malicious activity where an otherwise legitimate program might be compromised or used for covert communication.
This rule detects the launch of processes whose associated file hash (SHA256) has a low prevalence across the monitored environment. Specifically, it flags processes where the SHA256 hash has been observed on 1 to 3 distinct endpoints over the past 10 days. This can indicate the execution of rare or newly introduced executables, which could be malicious.
This rule detects when a file is downloaded from an IP address and subsequently created on a system, where both the file hash and the IP address are identified by VirusTotal Relationships as being associated with each other, specifically through a 'DOWNLOADED_FROM' relationship. This indicates that the downloaded file is known to have been served from that particular IP address, potentially flagging malicious file distribution.
This rule detects when a known malicious file, identified by its SHA256 hash through VirusTotal relationships, attempts to contact a domain that VirusTotal also associates with that file. It correlates DNS query events with VirusTotal intelligence to identify suspicious network communications originating from potentially compromised systems.
This rule identifies process and file creation events where the associated file's SHA256 hash is present in Google Safe Browsing data and has been observed for a duration greater than 7 days (604,800 seconds). This long observation period for a Safe Browsing-flagged hash could indicate persistent malware or a file that has been present on systems for an extended time before being flagged or detected.
The analytic detects the use of `reg.exe` to export Windows Registry hives, specifically `sam`, `system`, or `security`, which may contain sensitive credentials. This activity indicates potential offline credential access attacks, often executed from untrusted processes or scripts. If confirmed malicious, attackers could gain access to credential data, enabling further compromise and lateral movement within the network.
The analytic detects the usage of a renamed 7-Zip executable using Sysmon data. It leverages the OriginalFileName field to identify instances where the 7-Zip process has been renamed. This activity is significant as attackers often rename legitimate tools to evade detection while staging or exfiltrating data. If confirmed malicious, this behavior could indicate data exfiltration attempts or other unauthorized data manipulation, potentially leading to significant data breaches or loss of sensitive information. Analysts should validate the legitimacy of the 7-Zip executable and investigate parallel processes for further suspicious activities.
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