Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential unauthorized or suspicious configuration changes related to packet sniffer objects and associated authentication or management ports on FortiGate firewalls across multiple devices.
Detects potential unauthorized or suspicious configuration changes related to packet sniffer objects and associated authentication or management ports on FortiGate firewalls across multiple devices.
Detects potential unauthorized or suspicious configuration changes related to packet sniffer objects and associated authentication or management ports on FortiGate firewalls across multiple devices.
Detects potential unauthorized or suspicious configuration changes related to packet sniffer objects and associated authentication or management ports on FortiGate firewalls across multiple devices.
The following analytic detects the use of the curl command with specific switches (-F, --form, --upload-file, -T, -d, --data, --data-raw, -I, --head) to upload AWS credentials or configuration files to a remote destination. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions and process details. This activity is significant as it may indicate an attempt to exfiltrate sensitive AWS credentials, a technique known to be used by the TeamTNT group. If confirmed malicious, this could lead to unauthorized access and potential compromise of AWS resources.
The following analytic detects the use of the 'dd' command to overwrite files on a Linux system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs that include command-line details. This activity is significant because adversaries often use the 'dd' command to destroy or irreversibly overwrite files, disrupting system availability and services. If confirmed malicious, this behavior could lead to data destruction, making recovery difficult and potentially causing significant operational disruptions.
The following analytic detects the behavior of decoding base64-encoded data and passing it to a Linux shell. Additionally, it mitigates the potential damage and protects the organization's systems and data.The detection is made by searching for specific commands in the Splunk query, namely "base64 -d" and "base64 --decode", within the Endpoint.Processes data model. The analytic also includes a filter for Linux shells. The detection is important because it indicates the presence of malicious activity since Base64 encoding is commonly used to obfuscate malicious commands or payloads, and decoding it can be a step in running those commands. It suggests that an attacker is attempting to run malicious commands on a Linux system to gain unauthorized access, for data exfiltration, or perform other malicious actions.
The following analytic detects the use of 'curl' and 'wget' commands within a Linux environment. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, user information, and command-line executions. This activity is significant as 'curl' and 'wget' are commonly used for downloading files, which can indicate potential ingress of malicious tools. If confirmed malicious, this activity could lead to unauthorized code execution, data exfiltration, or further compromise of the system. Monitoring and tuning this detection helps identify and differentiate between normal and potentially harmful usage.
The following analytic identifies the use of the 'kmod' process to list kernel modules on a Linux system. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. While listing kernel modules is not inherently malicious, it can be a precursor to loading unauthorized modules using 'insmod'. If confirmed malicious, this activity could allow an attacker to load kernel modules, potentially leading to privilege escalation, persistence, or other malicious actions within the system.
Detects the execution of suspicious child processes (shells, interpreters, or system reconnaissance tools) directly spawned by critical Citrix NetScaler service binaries (nsppe, httpd, nsaaad). This behavior is indicative of post-exploitation activity, such as command injection or lateral movement following the exploitation of a public-facing NetScaler application vulnerability.
Identifies high Ollama runner counts and large model buffer allocations as possible resource pressure indicators. Memory values vary with model size and hardware, and these operational logs do not establish malicious intent; validate against host capacity and workload baselines.
Detects critical service crashes, fatal errors, and abnormal process terminations in Ollama that may indicate exploitation attempts, resource exhaustion attacks, malicious input triggering unhandled exceptions, or deliberate denial of service attacks designed to disrupt AI model availability and degrade system stability.
This rule monitors NetScaler Syslog events for file creation or modification actions targeting web-accessible directories (/netscaler/, /var/vpn/, /var/netscaler/logon/) involving common web shell scripting extensions (.php, .pl, .sh, .py). It is designed to detect post-exploitation activity such as the manual deployment of backdoors following a vulnerability compromise.
This rule detects indicators of the PitScaler campaign targeting Citrix NetScaler ADC and Gateway appliances, exploiting vulnerabilities (CVE-2026-88771, CVE-2026-88772). It identifies the full attack chain including initial DTLS heap corruption exploitation, WHIPSHOT web shell C2 patterns, SLAPSHOT tunneling artifacts, web shell deployment files, httpd.conf PHP configuration tampering for persistence, privilege escalation via setuid /bin/sh modification, and anti-forensic log tampering.
The following analytic detects the creation of new user accounts on Linux systems using commands like "useradd" or "adduser." It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as adversaries often create new user accounts to establish persistence on compromised hosts. If confirmed malicious, this could allow attackers to maintain access, escalate privileges, and further compromise the system, posing a severe security risk.
The following analytic detects the use of the Linux 'xclip' command to copy data from the clipboard. It leverages Endpoint Detection and Response (EDR) telemetry, focusing on process names and command-line arguments related to clipboard operations. This activity is significant because adversaries can exploit clipboard data to capture sensitive information such as passwords or IP addresses. If confirmed malicious, this technique could lead to unauthorized data exfiltration, compromising sensitive information and potentially aiding further attacks within the environment.
The following analytic detects the insertion of a Linux kernel module using the insmod utility. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs that include process names and command-line details. This activity is significant as it may indicate the installation of a rootkit or malicious kernel module, potentially allowing an attacker to gain elevated privileges and bypass security detections. If confirmed malicious, this could lead to unauthorized code execution, persistent access, and severe compromise of the affected system.
The following analytic detects the use of the base64 decode command on Linux systems, which is often used to deobfuscate files. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions that include "base64 -d" or "base64 --decode". This activity is significant as it may indicate an attempt to hide malicious payloads or scripts. If confirmed malicious, an attacker could use this technique to execute hidden code, potentially leading to unauthorized access, data exfiltration, or further system compromise.
The following analytic detects the execution of the SysReq hack to reboot a Linux system host. It leverages Endpoint Detection and Response (EDR) data to identify processes executing the command to pipe 'b' to /proc/sysrq-trigger. This activity is significant as it is an uncommon method to reboot a system and was observed in the Awfulshred malware wiper. If confirmed malicious, this technique could indicate the presence of suspicious processes and potential system compromise, leading to unauthorized reboots and disruption of services.
Detects suspicious post-exploitation behaviors on Citrix NetScaler appliances, specifically tracking the modification of file permissions to grant setuid/setgid bits to the shell and the termination of httpd processes often associated with webshell persistence or manipulation.
This rule detects indicators of the PitScaler campaign targeting Citrix NetScaler ADC and Gateway appliances, exploiting vulnerabilities (CVE-2026-88771, CVE-2026-88772). It identifies the full attack chain including initial DTLS heap corruption exploitation, WHIPSHOT web shell C2 patterns, SLAPSHOT tunneling artifacts, web shell deployment files, httpd.conf PHP configuration tampering for persistence, privilege escalation via setuid /bin/sh modification, and anti-forensic log tampering.
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