This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.

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The following analytic detects anonymous and unauthenticated requests to a Kubernetes cluster. It identifies this behavior by monitoring for API calls from users who have not provided any token or password in their request. This is a significant behavior to identify for a SOC as it indicates a severe misconfiguration that allows unfettered access to a cluster with no traceability to a user or service. The impact of such an attack could be substantial, potentially granting an attacker access to sensitive data or control over the cluster. This detection rule is crucial for maintaining the security and integrity of your Kubernetes infrastructure.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2023-12-19
  • Author: Rod Soto, Patrick Bareiss, Splunk
  • ID: 042a3d32-8318-4763-9679-09db2644a8f2


Kill Chain Phase
  • DE.AE
  • CIS 10
`kube_audit` user.username="system:anonymous" user.groups{} IN ("system:unauthenticated") 
| fillnull 
| stats count by objectRef.name objectRef.namespace objectRef.resource requestReceivedTimestamp requestURI responseStatus.code sourceIPs{} stage user.groups{} user.uid user.username userAgent verb 
| rename sourceIPs{} as src_ip, user.username as user 


The SPL above uses the following Macros:

:information_source: kubernetes_aws_detect_suspicious_kubectl_calls_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • objectRef.resource
  • verb
  • objectRef.name
  • objectRef.namespace
  • requestReceivedTimestamp
  • requestURI
  • responseStatus.code
  • sourceIPs{}
  • stage
  • user.groups{}
  • user.uid
  • user.username
  • userAgent
  • verb

How To Implement

You must install splunk AWS add on and Splunk App for AWS. This search works with cloudwatch logs.

Known False Positives

Kubectl calls are not malicious by nature. However source IP, verb and Object can reveal potential malicious activity, specially anonymous suspicious IPs and sensitive objects such as configmaps or secrets

Associated Analytic Story


Risk Score Impact Confidence Message
25.0 50 50 tbd

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.


Test Dataset

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

source | version: 2