Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
219 detections
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This analytic identifies anomalously high outbound network activity from processes within Kubernetes containerized workloads. It compares recent network metrics (TCP/UDP bytes, new sockets, packets) over the last hour against the average metrics from the past 30 days. Significant deviations may indicate data exfiltration, process modification, or container compromise, potentially leading to unauthorized data transfer or further attacks within the containerized environment.
The analytic identifies anomalous inbound network traffic volumes from processes within containerized workloads. It leverages Network Performance Monitoring metrics collected via an OTEL collector and pulled from Splunk Observability Cloud. The detection compares recent metrics (tcp.bytes, tcp.new_sockets, tcp.packets, udp.bytes, udp.packets) over the last hour with the average over the past 30 days. This activity is significant as it may indicate unauthorized data reception, potential breaches, vulnerability exploitation, or malware propagation. If confirmed malicious, it could lead to command and control installation, data integrity damage, container escape, and further environment compromise.
This analytic detects new UDP communication between a source and destination workload pair within a Kubernetes cluster. It uses Network Performance Monitoring (NPM) metrics from an OTEL collector via Splunk Observability Cloud. The detection compares network activity over the last hour with the past 30 days to identify new inter-workload communication. Such changes in network behavior can indicate potential security threats or anomalies, including unauthorized connections that may lead to data breaches, privilege escalation, lateral movement, or disruption of critical services.
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.
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 attempts to execute remote commands within a Kubernetes Pod's container, typically using the 'kubectl exec' command. This activity is logged as a 'create' verb on the 'pods' resource with the 'exec' subresource in Kubernetes audit logs.
Detects attempts by an identity to enumerate its Kubernetes Role-Based Access Control (RBAC) permissions. This activity is often observed in the early stages of a breach as attackers try to understand their access within a compromised Kubernetes environment. This can be achieved by querying the Kubernetes API server's SelfSubjectRulesReview API, for example, using the "kubectl auth can-i --list" command.
Detects attempts to enumerate Kubernetes secrets, which could indicate an adversary is searching for sensitive information like API keys, tokens, or other credentials stored within the cluster.
Detects attempts to inject a sidecar container into a running Kubernetes deployment. This is achieved by monitoring for 'patch' operations on 'deployments' resources within the 'apps' API group. An attacker might use this technique to run their code and hide activity within a legitimate pod, rather than deploying a separate, potentially more conspicuous, pod.
Identifies when a service account in Azure Kubernetes Service is modified or deleted. This could indicate an adversary attempting to disrupt services, remove access, or manipulate accounts for persistence or privilege escalation within the Kubernetes cluster.
Detects the modification or deletion of Kubernetes RoleBindings or ClusterRoleBindings within Azure Kubernetes Service. These actions can indicate an adversary attempting to escalate privileges, maintain persistence, or disrupt services by altering access control configurations.
Detects when a Kubernetes CronJob or Job is created, modified, or deleted. 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.
This rule identifies when an Azure Kubernetes network policy is modified or deleted. Network policies control the traffic flow between pods/namespaces and to/from external network endpoints. Unauthorized modification or deletion of these policies can lead to security vulnerabilities, such as allowing unauthorized network access to sensitive services or disrupting legitimate communication within the cluster, potentially leading to a denial of service or data exfiltration.
This rule detects the creation of a Kubernetes container that includes a hostPath mount. A hostPath volume allows a directory or file from the node to be mounted directly into the container. Attackers with permissions to create pods can leverage writable hostPath volumes to perform container escapes, potentially gaining access to the underlying host node by using techniques like chroot.
Detects the creation of a "privileged" container in Kubernetes. A privileged container has root capabilities on the host, allowing it to access and modify host processes, network operations, IPC calls, file system, mount points, and SELinux configurations. This action can indicate a threat actor attempting container breakout or privilege escalation. The rule specifically looks for 'create' verbs on 'pods' resources where 'capabilities' are present, which implies elevated privileges.
Detects when an Azure Kubernetes Cluster is created or deleted. This activity can indicate significant infrastructure changes, either legitimate or malicious. Monitoring these operations is crucial for maintaining the security and integrity of containerized environments.
Detects the removal of a deployment from a Kubernetes cluster. This could indicate disruptive activity aiming to impact business operations.
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