Kubernetes Process with Resource Ratio Anomalies
The following analytic detects anomalous changes in resource utilization ratios for processes running on a Kubernetes node. It leverages process metrics collected via an OTEL collector and hostmetrics receiver,…
Description
The following analytic detects anomalous changes in resource utilization ratios for processes running on a Kubernetes node. It leverages process metrics collected via an OTEL collector and hostmetrics receiver, analyzed through Splunk Observability Cloud. The detection uses a lookup table containing average and standard deviation values for various resource ratios (e.g., CPU:memory, CPU:disk operations). Significant deviations from these baselines may indicate compromised processes, malicious activity, or misconfigurations. If confirmed malicious, this could signify a security breach, allowing attackers to manipulate workloads, potentially leading to data exfiltration or service disruption.
Detection logic
Detection requirements
- Platform
- ContainersIaaSLinuxmacOSWindows
The rule states no platform. This is derived from the ATT&CK technique it maps to.
Known benign triggers
- No false positives have been identified at this time.
MITRE ATT&CK mappings
0 exclusive techniques.This is coverage no other published rule has; it is not this rule's total technique count.
References
| Reference | Cited by |
|---|---|
| github.com/signalfx/splunk-otel-collector-chart | 12 |
From the source
- At source
- Open at source
- Upstream identifier
- 0d42b295-0f1f-4183-b75e-377975f47c65
- Tagged by the source as
- Abnormal Kubernetes Behavior using Splunk Infrastructure MonitoringKubernetescloudSplunk CloudSplunk EnterpriseSplunk Enterprise Securitynetwork
Licence
- Published under
- Apache License 2.0Read the licence
- Attribution
- Required
- Obtained under
- Apache-2.0Read the origin licence
Authorship
- Written by
- Published
- Aug 26, 2026
- Version
- 1