Detection: Kubernetes GCP detect suspicious kubectl calls

DEPRECATED DETECTION

This detection has been marked as deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported. If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2024-10-17 ID: a5bed417-070a-41f2-a1e4-82b6aa281557 Author: Rod Soto, Splunk Type: Hunting Product: Splunk Enterprise Security

Description

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

Search

1`google_gcp_pubsub_message` data.protoPayload.requestMetadata.callerSuppliedUserAgent=kubectl* src_user=system:unsecured OR src_user=system:anonymous 
2| table src_ip src_user data.protoPayload.requestMetadata.callerSuppliedUserAgent data.protoPayload.authorizationInfo{}.granted object_path 
3|dedup src_ip src_user 
4|`kubernetes_gcp_detect_suspicious_kubectl_calls_filter`

Data Source

No data sources specified for this detection.

Macros Used

Name	Value
google_gcp_pubsub_message	`sourcetype="google:gcp:pubsub:message"`
kubernetes_gcp_detect_suspicious_kubectl_calls_filter	`search *`

kubernetes_gcp_detect_suspicious_kubectl_calls_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK

+ Kill Chain Phases

+ NIST

+ CIS

- Threat Actors

ID	Technique	Tactic

NistCategory.DE_AE

Cis18Value.CIS_10

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting	Value
Disabled	true
Cron Schedule	`0 * * * *`
Earliest Time	`-70m@m`
Latest Time	`-10m@m`
Schedule Window	`auto`
Creates Risk Event	False

This configuration file applies to all detections of type hunting.

Implementation

You must install splunk add on for GCP. This search works with pubsub messaging logs.

Known False Positives

Kubectl calls are not malicious by nature. However source IP, source user, user agent, object path, and authorization context can reveal potential malicious activity, specially anonymous suspicious IPs and sensitive objects such as configmaps or secrets

Associated Analytic Story

Kubernetes Sensitive Object Access Activity

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
tbd	25	50	50

The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	Not Applicable	N/A	N/A	N/A
Unit	❌ Failing	N/A	`N/A`	`N/A`
Integration	❌ Failing	N/A	`N/A`	`N/A`

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: GitHub | Version: 3