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Description

The following analytic detects unauthorized access or misuse of Kubernetes Secrets from unusual locations. It identifies anomalies in access patterns by segmenting and analyzing the source of requests by country. Kubernetes Secrets, which store sensitive information like passwords, OAuth tokens, and SSH keys, are critical assets, and their misuse can lead to significant security breaches. This behavior is worth identifying for a SOC as it could indicate an attacker attempting to exfiltrate or misuse these secrets. The impact of such an attack could be severe, potentially leading to unauthorized access to sensitive systems or data.

  • Type: Anomaly

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

  • Last Updated: 2023-12-06
  • Author: Patrick Bareiss, Splunk
  • ID: 40a064c1-4ec1-4381-9e35-61192ba8ef82

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1552.007 Container API Credential Access
Kill Chain Phase
  • Exploitation
NIST
  • DE.AE
CIS20
  • CIS 13
CVE 


1
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`kube_audit` objectRef.resource=secrets verb=get 
| iplocation sourceIPs{} 
| fillnull 
| search NOT `kube_allowed_loactions` 
| stats count by objectRef.name objectRef.namespace objectRef.resource requestReceivedTimestamp requestURI responseStatus.code sourceIPs{} stage user.groups{} user.uid user.username userAgent verb City Country 
| rename sourceIPs{} as src_ip, user.username as user 
| `kubernetes_abuse_of_secret_by_unusual_location_filter`

Macros

The SPL above uses the following Macros:

:information_source: kubernetes_abuse_of_secret_by_unusual_location_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.

  • objectRef.resource
  • verb
  • objectRef.name
  • objectRef.namespace
  • requestReceivedTimestamp
  • requestURI
  • responseStatus.code
  • sourceIPs{}
  • stage
  • user.groups{}
  • user.uid
  • user.username
  • userAgent
  • verb

How To Implement

The detection is based on data that originates from Kubernetes Audit logs. Ensure that audit logging is enabled in your Kubernetes cluster. Kubernetes audit logs provide a record of the requests made to the Kubernetes API server, which is crucial for monitoring and detecting suspicious activities. Configure the audit policy in Kubernetes to determine what kind of activities are logged. This is done by creating an Audit Policy and providing it to the API server. Use the Splunk OpenTelemetry Collector for Kubernetes to collect the logs. This doc will describe how to collect the audit log file https://github.com/signalfx/splunk-otel-collector-chart/blob/main/docs/migration-from-sck.md.

Known False Positives

unknown

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
49.0 70 70 Access of Kubernetes secret $objectRef.name$ from unusual location $Country$ by $user$

: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

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