Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
1,418 detections
Filters
Last updated
All Time
Detection languages
529
347
171
163
130
Contributors
458
316
172
104
97
Categories
877
668
225
183
158
Platforms
1,330
232
183
47
31
Products / Services
10,650
9,755
6,688
4,418
3,745
1,418
MITRE Techniques
449
435
337
325
200
CVEs
28
22
10
9
7
Detects identities attempting to enumerate their Kubernetes RBAC permissions.
In the early stages of a breach, attackers will aim to list the permissions they have within the compromised environment.
In a Kubernetes cluster, this can be achieved by interacting with the API server, and querying the SelfSubjectAccessReview API via e.g. a "kubectl auth can-i --list" command.
This will enumerate the Role-Based Access Controls (RBAC) rules defining the compromised user's authorization.
In the early stages of a breach, attackers will aim to list the permissions they have within the compromised environment.
In a Kubernetes cluster, this can be achieved by interacting with the API server, and querying the SelfSubjectAccessReview API via e.g. a "kubectl auth can-i --list" command.
This will enumerate the Role-Based Access Controls (RBAC) rules defining the compromised user's authorization.
Detects the execution of the 'esxcli' command with the 'storage' flag to retrieve information about storage status on VMware ESXi systems. This activity has been observed in malware campaigns, including DarkSide and LockBit ransomware.
This rule detects suspicious usage of the 'curl' command on Linux systems that indicates a file upload or data transfer to a web service. It specifically looks for the 'curl' executable being run with command-line arguments such as '--form', '--upload-file', '--data', or their variations ('--data-ascii', '--data-binary', '--data-raw', '--data-urlencode'), or the shorthand options '-F', '-T', '-d'. The rule filters out connections to localhost or 127.0.0.1 to reduce false positives from legitimate local development or testing activities.
This rule detects the execution of common archiving utilities (zip, gzip, tar) on Linux systems. Adversaries often compress data prior to exfiltration to reduce its size and make it easier to transfer. This rule specifically looks for the 'execve' system call with 'zip', 'gzip -k', or 'tar -c' as the primary command and arguments.
Detects the execution of the 'mount' command with the 'hidepid=2' option. This parameter is used to hide processes from other users on the system, which can be leveraged by adversaries for defense evasion by making their malicious processes less visible.
Detects when a Kubernetes CronJob or Job is created or modified.
A Kubernetes Job creates one or more pods to accomplish a specific task, and a CronJob creates Jobs on a recurring schedule.
An adversary can take advantage of this Kubernetes object to schedule Jobs to run containers that execute malicious code within a cluster, allowing them to achieve persistence.
A Kubernetes Job creates one or more pods to accomplish a specific task, and a CronJob creates Jobs on a recurring schedule.
An adversary can take advantage of this Kubernetes object to schedule Jobs to run containers that execute malicious code within a cluster, allowing them to achieve persistence.
Detects a suspicious curl process start the adds a file to a web request
This analytic aggregates and summarizes alerts from Microsoft Defender for Endpoint. It extracts details such as source, file name, severity, process command line, IP address, registry key, signature, description, and unique ID. The detection is not intended to identify new activity from raw data but rather to leverage existing Microsoft Defender for Endpoint alerts for correlation and risk-based alerting. It filters out alerts with a 'clean' verdict and dynamically maps MITRE techniques and assigns risk scores based on the alert's severity.
Detects creation of new Kubernetes service account, which could indicate an attacker's attempt to persist within a cluster.
This 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 the suspicious editing of cron jobs in Linux using the crontab command-line parameter (-e). It identifies this activity by monitoring command-line executions involving 'crontab' and the edit parameter. This behavior is significant for a SOC as cron job manipulations can indicate unauthorized persistence attempts or scheduled malicious actions. If confirmed malicious, this activity could lead to system compromise, unauthorized access, or broader network compromise.
The following analytic detects the execution of the 'doas' tool on a Linux host. This tool allows standard users to perform tasks with root privileges, similar to 'sudo'. The detection leverages data from Linux Auditd, focusing on process names and command-line executions. This activity is significant as 'doas' can be exploited by adversaries to gain elevated privileges on a compromised host. If confirmed malicious, this could lead to unauthorized administrative access, potentially compromising the entire system.
The following analytic detects suspicious use of the `rmmod` utility for kernel module removal, which may indicate an attacker attempt to unload critical or security-related kernel modules. The `rmmod` command is used to remove modules from the Linux kernel, and unauthorized use can be a tactic to disable security features, conceal malicious activities, or disrupt system operations. By monitoring for unusual or unauthorized `rmmod` activity, this analytic helps identify potential tampering with kernel modules, enabling security teams to take proactive measures to protect system integrity and security.
The following analytic identifies the use of the 'lsmod' command to list kernel modules on a Linux system. This detection leverages data from Linux Auditd, 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.
The following analytic detects the execution of the "At" application in Linux, which can be used by attackers to create persistence entries on a compromised host. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and parent process names associated with "at" or "atd". This activity is significant because the "At" application can be exploited to maintain unauthorized access or deliver additional malicious payloads. If confirmed malicious, this behavior could lead to data theft, ransomware attacks, or other severe consequences. Immediate investigation is required to determine the legitimacy of the execution and mitigate potential risks.
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.
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 identifies when a new device is enrolled on an Okta account. It uses OktaIm2 logs ingested via the Splunk Add-on for Okta Identity Cloud to detect the creation of new device enrollments. This activity is significant as it may indicate a legitimate user settinging up a new device or an adversary adding a device to maintain unauthorized access. If confirmed malicious, this could lead to potential account takeover, unauthorized access, and persistent control over the compromised Okta account. Monitoring this behavior is crucial for detecting and mitigating unauthorized access attempts.
This correlation rule identifies when a user exceeds a predefined risk threshold based on multiple suspicious Okta activities within a 24-hour period. It aggregates risk events from "Suspicious Okta Activity," "Okta Account Takeover," and "Okta MFA Exhaustion" analytic stories. The detection is significant as it highlights potentially compromised user accounts exhibiting multiple tactics, techniques, and procedures (TTPs). If confirmed malicious, this activity could indicate a serious security breach, allowing attackers to gain unauthorized access, escalate privileges, or persist within the environment.
The following analytic identifies suspicious command-line parameters associated with the use of Impacket's smbexec.py for lateral movement. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line patterns indicative of Impacket tool usage. This activity is significant as both Red Teams and adversaries use Impacket for remote code execution and lateral movement. If confirmed malicious, this activity could allow attackers to execute commands on remote endpoints, potentially leading to unauthorized access, data exfiltration, or further compromise of the network.
The following analytic detects suspicious file permission modifications using the `chmod` command, which may indicate an attacker attempting to alter access controls on critical files or directories. Such modifications can be used to grant unauthorized users elevated privileges or to conceal malicious activities by restricting legitimate access. By monitoring for unusual or unauthorized `chmod` usage, this analytic helps identify potential security breaches, allowing security teams to respond promptly to prevent privilege escalation, data tampering, or other unauthorized actions on the system.
Page 59 of 68