Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
7,138 detections
Filters
Last updated
All Time
Detection languages
3,224
1,086
498
476
469
Contributors
1,824
1,607
872
505
300
Categories
2,976
2,470
1,061
1,024
908
Platforms
39,790
7,138
6,515
3,861
3,597
Products / Services
1,325
1,067
970
655
490
MITRE Techniques
2,227
1,319
1,319
874
873
CVEs
66
65
33
32
28
IDS Classtypes
81
79
56
27
10
IDS Protocols
149
98
6
5
4
This analytic detects previously unseen processes within the Kubernetes environment on master or worker nodes. It leverages process metrics collected via an OTEL collector and hostmetrics receiver, with data pulled from Splunk Observability Cloud. The detection compares processes observed in the last hour against those seen in the previous 30 days. Identifying new processes is crucial as they may indicate unauthorized activity or attempts to compromise the node. If confirmed malicious, these processes could lead to data exfiltration, privilege escalation, denial-of-service attacks, or the introduction of malware, posing significant risks to the Kubernetes cluster.
The analytic detects the addition of NOPASSWD entries to the /etc/sudoers file on Linux systems. It leverages Linux Auditd data to identify command lines containing "NOPASSWD:". This activity is significant because it allows users to execute commands with elevated privileges without requiring a password, which can be exploited by adversaries to maintain persistent, privileged access. If confirmed malicious, this could lead to unauthorized privilege escalation, persistent access, and potential compromise of sensitive data and system integrity.
This analytic detects the execution of the 'setcap' utility to enable the SUID bit on Linux systems. It leverages Linux Auditd data, focusing on process names and command-line arguments that indicate the use of 'setcap' with specific capabilities. This activity is significant because setting the SUID bit allows a user to temporarily gain root access, posing a substantial security risk. If confirmed malicious, an attacker could escalate privileges, execute arbitrary commands with elevated permissions, and potentially compromise the entire system.
The following analytic detects suspicious modifications to cron jobs on Linux systems using the crontab command with list parameters. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as it may indicate an attempt to establish persistence or execute malicious code on a schedule. If confirmed malicious, the impact could include unauthorized code execution, data destruction, or other damaging outcomes. Further investigation should analyze the added cron job, its associated command, and any related processes.
This analytic identifies the execution of Node.js with elevated privileges using `sudo`, specifically when spawning child processes. It focuses on command-line executions that include specific Node.js commands related to `child_process.spawn` and `stdio`. Running Node.js as a superuser without dropping privileges can allow unauthorized access to the file system and potential privilege escalation. If confirmed malicious, this could enable an attacker to maintain privileged access, execute arbitrary code, and compromise sensitive data within the environment.
The analytic detects attempts to stop or clear a service on Linux systems. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on processes like "systemctl," "service," and "svcadm" executing stop commands. This activity is significant as adversaries often 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.
This detection identifies potential exploitation of CVE-2025-24813 in Apache Tomcat through the initial stage of the attack. This first phase occurs when an attacker attempts to upload a malicious serialized Java object with a .session file extension via an HTTP PUT request. When successful, these uploads typically result in HTTP status codes 201 (Created) or 409 (Conflict) and create the foundation for subsequent deserialization attacks by placing malicious content in a location where Tomcat's session management can access it.
The following analytic detects the creation of files in Linux init boot directories, which are used for automatic execution upon system startup. It leverages file system logs to identify new files in directories such as /etc/init.d/ and /etc/rc.d/. This activity is significant as it is a common persistence technique used by adversaries, malware authors, and red teamers. If confirmed malicious, this could allow an attacker to maintain persistence on the compromised host, potentially leading to further exploitation and unauthorized control over the system.
The analytic detects the use of Ngrok on a Linux operating system by monitoring process names and command-line arguments. Ngrok is a legitimate reverse proxy tool that can be used by adversaries to establish reverse proxies, potentially bypassing network defenses. If confirmed malicious, this could allow attackers to create persistent, unauthorized access channels, facilitating data exfiltration or further exploitation of the compromised system.
The following analytic identifies processes running from newly seen paths within a Kubernetes environment. It leverages process metrics collected via an OTEL collector and hostmetrics receiver, and data is pulled from Splunk Observability Cloud using the Splunk Infrastructure Monitoring Add-on. This detection compares processes observed in the last hour with those seen over the previous 30 days. This activity is significant as it may indicate unauthorized changes, compromised nodes, or the introduction of malicious software. If confirmed malicious, it could lead to unauthorized process execution, control over critical resources, data exfiltration, privilege escalation, or malware introduction within the Kubernetes cluster.
The following analytic detects unauthorized file creation in known crontab directories on Unix-based systems. It leverages filesystem data to identify new files in directories such as /etc/cron* and /var/spool/cron/*. This activity is significant as it may indicate an attempt by threat actors or malware to establish persistence on a compromised host. If confirmed malicious, this could allow attackers to execute arbitrary code at scheduled intervals, potentially leading to further system compromise and unauthorized access to sensitive information.
The following analytic detects suspicious attempts to find credentials stored in password managers, which may indicate an attacker's effort to retrieve sensitive login information. Password managers are often targeted by adversaries seeking to access stored passwords for further compromise or lateral movement within a network. By monitoring for unusual or unauthorized access to password manager files or processes, this analytic helps identify potential credential theft attempts, enabling security teams to respond quickly to protect critical accounts and prevent further unauthorized access.
The following analytic identifies the execution of common Linux processes used for elevation control, such as `chmod`, `chown`, and `setuid`. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant because these processes are often abused by adversaries to gain persistence or escalate privileges on compromised hosts. If confirmed malicious, this behavior could allow attackers to modify file attributes, change file ownership, or set user IDs, potentially leading to unauthorized access and control over critical system resources.
This analytic detects the creation of new files within the Linux kernel/driver directory. This activity is significant because this directory is typically reserved for kernel modules, and unauthorized file creation here can indicate a rootkit installation. If confirmed malicious, this could allow an attacker to gain high-level privileges, potentially compromising the entire system by executing code at the kernel level.
The analytic detects the execution of the SysRq hack to reboot a Linux system host. It identifies 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.
The following analytic detects potential access or modification of the /etc/sudoers file on a Linux system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on processes like "cat," "nano," "vim," and "vi" accessing the /etc/sudoers file. This activity is significant because the sudoers file controls user permissions for executing commands with elevated privileges. If confirmed malicious, an attacker could gain persistence or escalate privileges, compromising the security of the targeted host.
The analytic detects attempts to exploit the Baron Samedit vulnerability (CVE-2021-3156) by identifying the use of the "sudoedit -s \" command. This detection leverages logs from Linux systems, specifically searching for instances of the sudoedit command with the "-s" flag followed by a double quote. This activity is significant because it indicates an attempt to exploit a known vulnerability that allows attackers to gain root privileges. If confirmed malicious, this could lead to complete system compromise, unauthorized access to sensitive data, and potential data breaches.
This analytic identifies a heap-based buffer overflow in sudoedit by detecting Linux logs containing both "sudoedit" and "segfault" terms. This detection leverages Splunk to monitor for more than five occurrences of these terms on a single host within a specified timeframe. This activity is significant because exploiting this vulnerability (CVE-2021-3156) can allow attackers to gain root privileges, leading to potential system compromise, unauthorized access, and data breaches. If confirmed malicious, this could result in elevated privileges and full control over the affected system, posing a severe security risk.
The analytic detects the use of the 'chown' command to change a file owner to 'root' on a Linux system. This activity is significant as it may indicate an attempt to escalate privileges by adversaries, malware, or red teamers. If confirmed malicious, this action could allow an attacker to gain root-level access, leading to full control over the compromised host and potential persistence within the environment.
The following analytic detects the addition of NOPASSWD entries to the /etc/sudoers file on Linux systems. It leverages Endpoint Detection and Response (EDR) telemetry to identify command lines containing "NOPASSWD:". This activity is significant because it allows users to execute commands with elevated privileges without requiring a password, which can be exploited by adversaries to maintain persistent, privileged access. If confirmed malicious, this could lead to unauthorized privilege escalation, persistent access, and potential compromise of sensitive data and system integrity.
The analytic identifies shell activity (sh, bash, csh, tcsh) within the Kubernetes privilege scope on a worker node. It leverages process metrics from an OTEL collector hostmetrics receiver, specifically process.cpu.utilization and process.memory.utilization, pulled from Splunk Observability Cloud. This activity is significant as unauthorized shell processes can indicate potential security threats, providing attackers an entry point to compromise the node and the entire Kubernetes cluster. If confirmed malicious, this activity could lead to data theft, service disruption, privilege escalation, lateral movement, and further attacks, severely compromising the cluster's security and integrity.
Page 321 of 340