Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This analytic identifies network traffic directed to the Active Directory Web Services Protocol (ADWS) on port 9389. It leverages network traffic logs, focusing on source and destination IP addresses, application names, and destination ports. This activity is significant as ADWS is used to manage Active Directory, and unauthorized access could indicate malicious intent. If confirmed malicious, an attacker could manipulate Active Directory, potentially leading to privilege escalation, unauthorized access, or persistent control over the environment.
'This composite hunting query will highlight any HTTP traffic in CommonSecurityLog web proxies (such as ZScaler) that match known patterns used by red teaming tools potentially stolen from FireEye. Most FireEye red teaming tools are designed to mimic
legitimate API activity, false positives are common. This query includes a basic check to determine how common a hostname is in you environment, and allows you to modify this threshold to remove legitimate traffic from the query results.
This query contains only a subset of potential FireEye red team tool communications, and therefore should not be relied upon alone :) .'
legitimate API activity, false positives are common. This query includes a basic check to determine how common a hostname is in you environment, and allows you to modify this threshold to remove legitimate traffic from the query results.
This query contains only a subset of potential FireEye red team tool communications, and therefore should not be relied upon alone :) .'
This query surfaces devices that are in a specific IPAddressV4 subnet
'Identifies instances where Wazuh logged over 400 '403' Web Errors from one IP Address. To onboard Wazuh data into Sentinel please view: https://github.com/wazuh/wazuh-documentation/blob/master/source/azure/monitoring%20activity.rst'
Remote Monitoring and Management (RMM) programs are IT to manage remote endpoints. Attackers have begun to abuse these programs to persist or provide C2 channels.
https://github.com/jischell-msft/RemoteManagementMonitoringTools
https://github.com/jischell-msft/RemoteManagementMonitoringTools
This analytic detects suspicious modifications to Unix shell configuration files, such as `.bashrc` or `.profile`, which may indicate an attempt to alter system behavior or gain unauthorized access. Unauthorized changes to these files can be used to execute malicious commands, escalate privileges, or hide malicious activities. By monitoring for unusual or unauthorized modifications to shell configuration files, this analytic helps identify potential security threats, allowing security teams to respond quickly and mitigate risks.
The following analytic detects attempts to stop a service on Linux systems. It leverages data from Linux Auditd. This activity is significant as adversaries often stop or terminate security or critical services to disable defenses or disrupt operations, as seen in malware like Industroyer2. If confirmed malicious, this could lead to the disabling of security mechanisms, allowing attackers to persist, escalate privileges, or deploy destructive payloads, severely impacting system integrity and availability.
Detects a specific user agent string and host ('api.dropbox.com') associated with an APT40 Dropbox tool, indicating potential data exfiltration or command and control activity via Dropbox.
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.
Detects HTTP requests containing the URI pattern '/asp.asp?ui=' which is known to be used by the Chafer malware for command and control communication to receive data from its C2 server.
Detects potential Java webshell uploads to an SAP NetViewer server via HTTP POST requests with a 'Content-Type' of 'application/octet-stream' and URI stems containing '/irj/' and ending with '.jsp', '.class', or '.java'. This behavior might indicate exploitation of vulnerabilities like CVE-2025-31324, which allows remote code execution through webshells.
Detects the download of Ursnif malware based on specific URL patterns and a successful HTTP status code. The rule looks for URIs containing a forward slash, '.php?l=', and ending with '.cab', combined with an HTTP status code of 200, indicating a successful download.
Detects Ursnif C2 traffic by identifying specific URL patterns in proxy logs. The rule looks for URIs containing base64-like encoding indicators ('_2f', '_2b') in combination with specific file extensions and directory names ('.avi' and '/images/'). This combination is indicative of Ursnif malware's command and control communication.
Detects network communication patterns associated with the Turla ComRAT malware, specifically looking for HTTP/HTTPS requests containing '/index/index.php?h=' in the URI. This pattern is indicative of ComRAT's command and control (C2) communication.
The analytic identifies DNS queries to domains associated with the 3CX supply chain attack. This activity is significant because it can indicate a potential compromise stemming from the 3CX supply chain attack, which is known for distributing malicious software through trusted updates. If confirmed malicious, this activity could allow attackers to establish a foothold in the network, exfiltrate sensitive data, or further propagate malware, leading to extensive damage and data breaches.
Detects update checks performed by Advanced IP Scanner and Advanced Port Scanner utilities. These utilities are often used for network reconnaissance and can be considered Potentially Unwanted Applications (PUA) in some environments. The rule specifically looks for requests to '/checkupdate.php' with a set of specific query parameters, indicating an update check from these tools.
Detects POST requests to the F5 BIG-IP iControl Rest API "bash" endpoint, which allows the execution of commands on the BIG-IP. This activity can indicate an attacker exploiting a public-facing application to gain initial access and execute arbitrary commands.
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.
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