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Suspicious kubectl calls

You might need to investigate the source of calls to your Kubernetes API when doing the following:

Prerequisites 

In order to execute this procedure in your environment, the following data, services, or apps are required:

Example

Kubectl calls are not malicious by nature. However, examining the source IP addresses, source users, user agents, object paths, and authorizations of these calls can reveal potentially malicious activity, especially if you find anonymous, suspicious IP addresses trying to access sensitive objects, such as configmaps or secrets. You want to investigate anonymous kubectl calls on your network to determine if they represent a threat. 

To optimize the search shown below, you should specify an index and a time range.

AWS

  1. Ensure that your deployment is ingesting CloudWatch logs.
  2. Run the following search: 
sourcetype="aws:cloudwatchlogs:eks" userAgent=kubectl* sourceIPs{}!=<valid IP address> sourceIPs{}!=::1 src_user=system:anonymous  
| table src_ip src_user verb userAgent requestURI  
| stats count BY src_ip src_user verb userAgent requestURI 

Search explanation

The table provides an explanation of what each part of this search achieves. You can adjust this query based on the specifics of your environment.

Splunk Search Explanation

sourcetype="aws:cloudwatchlogs:eks" 

Search only AWS EKS Kubernetes data.

userAgent=kubectl* 

Find the string kubectl* to reveal the use of kubectl application, which carries out HTTP requests to the Kubernetes API.

sourceIPs{}!=<valid IP address> 

sourceIPs{}!=::1

Exclude a legitimate IP address or range of addresses from the search.

src_user=system:anonymous

Search for anonymous users.

| table src_ip src_user verb userAgent requestURI 

Display the results in a table with columns in the order shown. 

| stats count BY src_ip src_user verb userAgent requestURI 

Count the number of each unique combination of source IP address, user, user agent, and requests URI.

Azure

  1. Ensure that you have configured Kube-Audit data diagnostics.
  2. Run the following search:  
sourcetype=mscs:storage:blob:json category=kube-audit 
|spath input=properties.log 
|spath input=responseObject.metadata.annotations.kubectl.kubernetes.io/last-applied-configuration 
|search userAgent=kubectl* sourceIPs{}!=<valid IP address> sourceIPs{}!=::1 
|table sourceIPs{} verb userAgent user.groups{} objectRef.resource objectRef.namespace requestURI 
|rare sourceIPs{} verb userAgent user.groups{} objectRef.resource objectRef.namespace requestURI

Search explanation

The table provides an explanation of what each part of this search achieves. You can adjust this query based on the specifics of your environment.

Splunk Search Explanation

sourcetype:mscs:storage:blob:json 

Search only the source type mscs:storage:blob:json. 

category=kube-audit

Search the data source kube-audit from the diagnostic logs in Azure Cloud services.

| spath input=properties.log 

Extract fields from the properties Kube-Audit log.

| spath input=responseObject.metadata.annotations.kubectl.kubernetes.io/last-applied-configuration 

Return the field values of Kubectl calls. 

| search userAgent=kubectl* sourceIPs{}!=<valid IP address> sourceIPs{}!=::1 

Find the wildcard string kubectl* to reveal the use of kubectl application, which carries out HTTP requests to the Kubernetes API. Exclude a legitimate source IP address or range of addresses from the search.

| table sourceIPs{} verb userAgent user.groups{} objectRef.resource objectRef.namespace requestURI 

Display the results in a table with columns in the order shown. 

| are sourceIPs{} verb userAgent user.groups{} objectRef.resource objectRef.namespace 

Display the least common source IP addresses, requests verbs, user agents, user groups, targeted resources, and namespaces.

GCP

  1. Ensure that your deployment is ingesting Pub/Sub messaging logs.
  2. Run the following search:
sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerSuppliedUserAgent=kubectl* src_user=system:unsecured OR src_user=system:anonymous 
| table src_ip src_user data.protoPayload.requestMetadata.callerSuppliedUserAgent data.protoPayload.authorizationInfo{}.granted object_path 
| dedup src_ip src_user 

Search explanation

The table provides an explanation of what each part of this search achieves. You can adjust this query based on the specifics of your environment.

Splunk Search Explanation

sourcetype="google:gcp:pubsub:message" 

Search only GCP Pub/Sub messages.

data.protoPayload.requestMetadata.callerSuppliedUserAgent=kubectl* 

Find the string kubectl* to reveal the use of kubectl application, which carries out HTTP requests to the Kubernetes API.

src_user=system:unsecured OR src_user=system:anonymous

Search for unsecured or anonymous users.

| table src_ip src_user data.protoPayload.requestMetadata.callerSuppliedUserAgent data.protoPayload.authorizationInfo{}.granted object_path 

Display the results in a table with columns in the order shown. Values from source IP addresses, source users, user agent, authorization granted information and the path of the object accessed via kubectl calls

| dedup src_ip src_user 

Remove duplicate results from the same IPs and users.

Result

Kubectl is a tool that can do almost anything on a cluster, so it needs to be monitored. Unauthenticated calls indicate exposure of the API. Establishing security groups can limit API calls. Kubectl command strings can reveal malicious intent and likely access key compromise. Look at data such as geolocation, unusual users, unusual commands, request verbs, and object path.

For additional information about this search, such as its applicability to common frameworks and standards, see this project on GitHub.

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