| ID | Technique | Tactic |
|---|---|---|
| T1204 | User Execution | Execution |
Detection: Kubernetes Unauthorized Access
Description
The following analytic detects unauthorized access attempts to Kubernetes by analyzing Kubernetes audit logs. It identifies anomalies in access patterns by examining the source of requests and their response statuses. This activity is significant for a SOC as it may indicate an attacker attempting to infiltrate the Kubernetes environment. If confirmed malicious, such access could lead to unauthorized control over Kubernetes resources, potentially compromising sensitive systems or data within the cluster.
Search
1`kube_audit` verb=create responseStatus.reason=Forbidden
2| fillnull
3| stats count by objectRef.namespace objectRef.resource requestReceivedTimestamp requestURI responseStatus.code responseStatus.message sourceIPs{} stage user.groups{} user.uid user.username userAgent verb
4| rename sourceIPs{} as src_ip, user.username as user
5| `kubernetes_unauthorized_access_filter`
Data Source
| Name | Platform | Sourcetype | Source | Supported App |
|---|---|---|---|---|
| Kubernetes Audit |  Kubernetes |
'_json' |
'kubernetes' |
N/A |
Macros Used
| Name | Value |
|---|---|
| kube_audit | source="kubernetes" |
| kubernetes_unauthorized_access_filter | search * |
kubernetes_unauthorized_access_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
KillChainPhase.INSTALLATION
NistCategory.DE_AE
Cis18Value.CIS_13
LAPSUS$
Scattered Spider
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 | True |
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.
Implementation
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
unknown
Associated Analytic Story
Risk Based Analytics (RBA)
| Risk Message | Risk Score | Impact | Confidence |
|---|---|---|---|
| Unauthorized access to Kubernetes from user $user$ | 49 | 70 | 70 |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
References
Detection Testing
| Test Type | Status | Dataset | Source | Sourcetype |
|---|---|---|---|---|
| Validation | ✅ Passing | N/A | N/A | N/A |
| Unit | ✅ Passing | Dataset | kubernetes |
_json |
| Integration | ✅ Passing | Dataset | kubernetes |
_json |
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: 2