Kubernetes Azure detect suspicious kubectl calls
THIS IS A DEPRECATED DETECTION
This detection has been marked deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported.
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: 2024-08-15
- Author: Rod Soto, Splunk
- ID: 4b6d1ba8-0000-4cec-87e6-6cbbd71651b5
Annotations
ATT&CK
Kill Chain Phase
NIST
- DE.AE
CIS20
- CIS 10
CVE
Search
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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:
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 fields
List of fields required to use this analytic.
- _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 |
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: 2