Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of potential tunneling tools from temporary directories (/tmp, /dev/shm, /var/tmp) using characteristic CLI arguments such as --listen, --token, --obfs, and --ws-path, or the known binary name 'ingredi_ws'.
Detects process execution where a shell (such as bash, zsh, cmd, or powershell) is spawned by a skill or openclaw process, and subsequently performs download activities (e.g., using curl, wget, invoke-webrequest) or establishes persistence (e.g., via cron, systemd, registry run keys, schtasks).
Detects a potential TeamPCP infostealer execution chain where a bash shell running setup.sh or entrypoint.sh spawns curl with POST or upload arguments.
Detects deletion of a managed resource from the vault following privileged access to
it. Removing the resource destroys the record of which credentials existed and who
held them, which is both destructive and a way of covering the preceding access.
Treat the deletion as evidence tampering rather than as routine housekeeping unless
a decommissioning record exists.
Onboarding: PAM360 is ingested via Syslog (Bloo extractor 879).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=audit where sourcename='PAM360' and action='RESOURCE_DELETED'
| groupby user, targetuser, srcip, message
it. Removing the resource destroys the record of which credentials existed and who
held them, which is both destructive and a way of covering the preceding access.
Treat the deletion as evidence tampering rather than as routine housekeeping unless
a decommissioning record exists.
Onboarding: PAM360 is ingested via Syslog (Bloo extractor 879).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=audit where sourcename='PAM360' and action='RESOURCE_DELETED'
| groupby user, targetuser, srcip, message
Detects a system shell interpreter being spawned directly by a Celery worker process.
This behavior indicates a Python background task execution framework is evaluating raw string input through a shell execution context,
which is highly indicative of successful command or prompt injection exploitation against an LLM agent task.
This behavior indicates a Python background task execution framework is evaluating raw string input through a shell execution context,
which is highly indicative of successful command or prompt injection exploitation against an LLM agent task.
Detects the use of curl or wget commands targeting the Cloud Instance Metadata Service (IMDS) at 169.254.169.254 for credential theft, or performing file uploads and data exfiltration patterns.
The following analytic detects attempts to access or dump the contents of /etc/passwd and /etc/shadow files on Linux systems. It leverages data from Linux Auditd, focusing on processes like 'cat', 'nano', 'vim', and 'vi' accessing these files. This activity is significant as it may indicate credential dumping, a technique used by adversaries to gain persistence or escalate privileges. If confirmed malicious, privileges. If confirmed malicious, attackers could obtain hashed passwords for offline cracking, leading to unauthorized access and potential system compromise.
The following analytic detects the suspicious use of the whoami command, which may indicate an attacker trying to gather information about the current user account on a compromised system. The whoami command is commonly used to verify user privileges and identity, especially during initial stages of an attack to assess the level of access. By monitoring for unusual or unauthorized executions of whoami, this analytic helps in identifying potential reconnaissance activities, enabling security teams to take action before the attacker escalates privileges or conducts further malicious operations.
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 Linux Auditd 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 use of the 'dd' command to overwrite files on a Linux system. It leverages data from Linux Auditd telemetry, 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 suspicious file and directory discovery activities, which may indicate an attacker's effort to locate sensitive documents and files on a compromised system. This behavior often precedes data exfiltration, as adversaries seek to identify valuable or confidential information for theft. By identifying unusual or unauthorized attempts to browse or enumerate files and directories, this analytic helps security teams detect potential reconnaissance or preparatory actions by an attacker, enabling timely intervention to prevent data breaches or unauthorized access.
The following analytic detects the insertion of a Linux kernel module using the insmod utility. It leverages data from Linux Auditd, 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 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.
The following analytic detects suspicious system network configuration discovery activities, which may indicate an adversary's attempt to gather information about the network environment. Such actions typically involve commands or tools used to identify network interfaces, routing tables, and active connections. Detecting these activities is crucial, as they often precede more targeted attacks like lateral movement or data exfiltration. By identifying unusual or unauthorized network discovery efforts, this analytic helps security teams to swiftly detect and respond to potential reconnaissance operations, mitigating the risk of further compromise.
Detects potential abuse of the Linux Magic SysRq (System Request) key by adversaries with root or sufficient privileges to manipulate or destabilize a system.
Writing to /proc/sysrq-trigger can crash the system, kill processes, or bypass standard logging.
Monitoring SysRq abuse helps detect stealthy post-exploitation activity.
Correlate with related EXECVE or PROCTITLE events to identify the process or user responsible for the access or modification.
Writing to /proc/sysrq-trigger can crash the system, kill processes, or bypass standard logging.
Monitoring SysRq abuse helps detect stealthy post-exploitation activity.
Correlate with related EXECVE or PROCTITLE events to identify the process or user responsible for the access or modification.
Detects modifications to core NetScaler startup configuration files 'ns.conf' or 'rc.netscaler'. Attackers often target these files after initial access to establish persistence by injecting malicious commands, rewrite, or responder policies to maintain access to the appliance.
Detects potential misuse of SSH credentials by identifying successful SSH logins from source IP addresses that have not been observed in the previous 14 days, or successful SSH logins occurring within one hour of an authorized_keys file modification on the same host. This combination of behaviors is indicative of an adversary establishing or using persistence via SSH key manipulation.
Detects the use of standard Linux command-line utilities (e.g., cat, curl, vi) to read or reference sensitive cloud credential files or Kubernetes service account tokens. This behavior is a common indicator of credential theft or discovery activities following initial access to a Linux host.
Detects the spawning of shells, network utilities, or scripting interpreters from Citrix NetScaler processes (nsppe or httpd), which may indicate post-exploitation activity following an initial access vulnerability.
Detects command-line activity on a NetScaler appliance indicative of defense evasion by truncating, deleting, or disabling audit logs (ns.log) and syslog forwarding services. This activity often follows the exploitation of public-facing application vulnerabilities where an attacker seeks to hide their presence.
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