Name:Kubernetes Node Port Creation id:d7fc865e-b8a1-4029-a960-cf4403b821b6 version:3 date:2024-09-30 author:Patrick Bareiss, Splunk status:production type:Anomaly Description:The following analytic detects the creation of a Kubernetes NodePort service, which exposes a service to the external network. It identifies this activity by monitoring Kubernetes Audit logs for the creation of NodePort services. This behavior is significant for a SOC as it could allow an attacker to access internal services, posing a threat to the Kubernetes infrastructure's integrity and security. If confirmed malicious, this activity could lead to data breaches, service disruptions, or unauthorized access to sensitive information. Data_source:
-Kubernetes Audit
search:`kube_audit` "objectRef.resource"=services verb=create requestObject.spec.type=NodePort | fillnull | stats count values(user.groups{}) as user_groups by kind objectRef.name objectRef.namespace objectRef.resource requestObject.kind requestObject.spec.type responseStatus.code sourceIPs{} stage user.username userAgent verb | rename sourceIPs{} as src_ip, user.username as user | `kubernetes_node_port_creation_filter`
how_to_implement:The detection is based on data that originates from Kubernetes Audit logs. Ensure that audit logging is enabled in your Kubernetes cluster. Kubernetes audit logs provide a record of the requests made to the Kubernetes API server, which is crucial for monitoring and detecting suspicious activities. Configure the audit policy in Kubernetes to determine what kind of activities are logged. This is done by creating an Audit Policy and providing it to the API server. Use the Splunk OpenTelemetry Collector for Kubernetes to collect the logs. This doc will describe how to collect the audit log file https://github.com/signalfx/splunk-otel-collector-chart/blob/main/docs/migration-from-sck.md. When you want to use this detection with AWS EKS, you need to enable EKS control plane logging https://docs.aws.amazon.com/eks/latest/userguide/control-plane-logs.html. Then you can collect the logs from Cloudwatch using the AWS TA https://splunk.github.io/splunk-add-on-for-amazon-web-services/CloudWatchLogs/. known_false_positives:unknown References: -https://kubernetes.io/docs/tasks/debug/debug-cluster/audit/ drilldown_searches: name:'View the detection results for - "$user$"' search:'%original_detection_search% | search user = "$user$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$user$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' tags: analytic_story: - 'Kubernetes Security' asset_type:Kubernetes confidence:70 impact:70 message:Kubernetes node port creation from user $user$ mitre_attack_id: - 'T1204' observable: name:'user' type:'User' - role: - 'Victim' name:'src_ip' type:'IP Address' - role: - 'Attacker' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' required_fields: - 'user.groups{}' - 'kind' - 'objectRef.name' - 'objectRef.namespace' - 'objectRef.resource' - 'requestObject.kind' - 'requestObject.spec.type' - 'responseStatus.code' - 'sourceIPs{}' - 'stage' - 'user.username' - 'userAgent' - 'verb' risk_score:49 security_domain:network