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Description

This search provides information on rare Kubectl calls with IP, verb namespace and object access context

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

  • Last Updated: 2020-05-26
  • Author: Rod Soto, Splunk
  • ID: 4b6d1ba8-0000-4cec-87e6-6cbbd71651b5

Annotations

ATT&CK
Kill Chain Phase
  • Exploitation
NIST
CIS20
CVE
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`kubernetes_azure` category=kube-audit 
| spath input=properties.log 
| spath input=responseObject.metadata.annotations.kubectl.kubernetes.io/last-applied-configuration 
| search userAgent=kubectl* sourceIPs{}!=127.0.0.1 sourceIPs{}!=::1 
| table sourceIPs{} verb userAgent user.groups{} objectRef.resource objectRef.namespace requestURI 
| rare sourceIPs{} verb userAgent user.groups{} objectRef.resource objectRef.namespace requestURI 
|`kubernetes_azure_detect_suspicious_kubectl_calls_filter`

Macros

The SPL above uses the following Macros:

:information_source: kubernetes_azure_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 field

  • _time

How To Implement

You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics

Known False Positives

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

Associated Analytic story

RBA

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.

Reference

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: 1