:warning: THIS IS A EXPERIMENTAL DETECTION

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.

Try in Splunk Security Cloud

Description

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

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

  • Last Updated: 2020-06-23
  • Author: Rod Soto, Splunk
  • ID: 042a3d32-8318-4763-9679-09db2644a8f2

Annotations

ATT&CK
Kill Chain Phase
  • Exploitation
NIST
CIS20
CVE
1
2
3
4
`aws_cloudwatchlogs_eks` userAgent=kubectl* sourceIPs{}!=127.0.0.1 sourceIPs{}!=::1 src_user=system:anonymous  
| table  src_ip src_user verb userAgent requestURI  
| stats  count by src_ip src_user verb userAgent requestURI 
|`kubernetes_aws_detect_suspicious_kubectl_calls_filter`

Macros

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.

  • _time
  • userAgent
  • sourceIPs{}
  • src_user
  • src_ip
  • verb
  • requestURI

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

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