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The following analytic detects unauthorized access or misuse of Kubernetes Secrets by unusual user names. It leverages Kubernetes Audit logs to identify anomalies in access patterns by analyzing the source of requests based on user names. This activity is significant for a SOC as Kubernetes Secrets store sensitive information like passwords, OAuth tokens, and SSH keys, making them critical assets. If confirmed malicious, this activity could lead to unauthorized access to sensitive systems or data, potentially resulting in significant security breaches and exfiltration of sensitive information.

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

  • Last Updated: 2024-05-27
  • Author: Patrick Bareiss, Splunk
  • ID: df6e9cae-5257-4a34-8f3a-df49fa0f5c46




ID Technique Tactic
T1552.007 Container API Credential Access
Kill Chain Phase
  • Exploitation
  • DE.AE
  • CIS 13
`kube_audit` objectRef.resource=secrets verb=get 
| search NOT `kube_allowed_user_names` 
| fillnull 
| stats count by 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 
| `kubernetes_abuse_of_secret_by_unusual_user_name_filter`


The SPL above uses the following Macros:

:information_source: kubernetes_abuse_of_secret_by_unusual_user_name_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.namespace
  • requestReceivedTimestamp
  • requestURI
  • responseStatus.code
  • sourceIPs{}
  • stage
  • user.groups{}
  • user.uid
  • user.username
  • userAgent
  • verb

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

Known False Positives


Associated Analytic Story


Risk Score Impact Confidence Message
49.0 70 70 Access of Kubernetes secret $$ from unusual user name $user$

: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 tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

source | version: 2