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splunk_escuAnomaly

Kubernetes Access Scanning

The following analytic detects potential scanning activities within a Kubernetes environment. It identifies unauthorized access attempts, probing of public APIs, or attempts to exploit known vulnerabilities by monitoring Kubernetes audit logs for repeated failed access attempts or unusual API requests. This activity is significant for a SOC as it may indicate an attacker's preliminary reconnaissance to gather information about the system. If confirmed malicious, this activity could lead to unauthorized access to sensitive systems or data, posing a severe security risk.

MITRE ATT&CK

Detection Query

`kube_audit` "user.groups{}"="system:unauthenticated" "responseStatus.code"=403
  | iplocation sourceIPs{}
  | stats count values(userAgent) as userAgent values(user.username) as user.username values(user.groups{}) as user.groups{} values(verb) as verb values(requestURI) as requestURI values(responseStatus.code) as responseStatus.code values(responseStatus.message) as responseStatus.message values(responseStatus.reason) as responseStatus.reason values(responseStatus.status) as responseStatus.status
    BY sourceIPs{} Country City
  | where count > 5
  | rename sourceIPs{} as src_ip, user.username as user
  | `kubernetes_access_scanning_filter`

Author

Patrick Bareiss, Splunk

Created

2026-03-10

Data Sources

Kubernetes Audit

Tags

Kubernetes Security
Raw Content
name: Kubernetes Access Scanning
id: 2f4abe6d-5991-464d-8216-f90f42999764
version: 8
date: '2026-03-10'
author: Patrick Bareiss, Splunk
status: production
type: Anomaly
description: The following analytic detects potential scanning activities within a Kubernetes environment. It identifies unauthorized access attempts, probing of public APIs, or attempts to exploit known vulnerabilities by monitoring Kubernetes audit logs for repeated failed access attempts or unusual API requests. This activity is significant for a SOC as it may indicate an attacker's preliminary reconnaissance to gather information about the system. If confirmed malicious, this activity could lead to unauthorized access to sensitive systems or data, posing a severe security risk.
data_source:
    - Kubernetes Audit
search: |-
    `kube_audit` "user.groups{}"="system:unauthenticated" "responseStatus.code"=403
      | iplocation sourceIPs{}
      | stats count values(userAgent) as userAgent values(user.username) as user.username values(user.groups{}) as user.groups{} values(verb) as verb values(requestURI) as requestURI values(responseStatus.code) as responseStatus.code values(responseStatus.message) as responseStatus.message values(responseStatus.reason) as responseStatus.reason values(responseStatus.status) as responseStatus.status
        BY sourceIPs{} Country City
      | where count > 5
      | rename sourceIPs{} as src_ip, user.username as user
      | `kubernetes_access_scanning_filter`
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. When you want to use this detection with AWS EKS, you need to enable EKS control plane logging https://docs.aws.amazon.com/eks/latest/userguide/control-plane-logs.html. Then you can collect the logs from Cloudwatch using the AWS TA https://splunk.github.io/splunk-add-on-for-amazon-web-services/CloudWatchLogs/.
known_false_positives: No false positives have been identified at this time.
references:
    - https://kubernetes.io/docs/tasks/debug/debug-cluster/audit/
drilldown_searches:
    - name: View the detection results for - "$user$"
      search: '%original_detection_search% | search  user = "$user$"'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$user$"
      search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$") starthoursago=168  | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
rba:
    message: Kubernetes scanning from ip $src_ip$
    risk_objects:
        - field: user
          type: user
          score: 20
    threat_objects:
        - field: src_ip
          type: ip_address
tags:
    analytic_story:
        - Kubernetes Security
    asset_type: Kubernetes
    mitre_attack_id:
        - T1046
    product:
        - Splunk Enterprise
        - Splunk Enterprise Security
        - Splunk Cloud
    security_domain: network
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1046/kubernetes_scanning/kubernetes_scanning.json
          sourcetype: _json
          source: kubernetes