Kubernetes Anomalous Inbound Network Activity from Process
The following analytic identifies anomalous inbound network traffic volumes from processes within containerized workloads. It leverages Network Performance Monitoring metrics collected via an OTEL collector and…
Description
The following analytic identifies anomalous inbound network traffic volumes from processes within containerized workloads. It leverages Network Performance Monitoring metrics collected via an OTEL collector and pulled from Splunk Observability Cloud. The detection compares recent metrics (tcp.bytes, tcp.new_sockets, tcp.packets, udp.bytes, udp.packets) over the last hour with the average over the past 30 days. This activity is significant as it may indicate unauthorized data reception, potential breaches, vulnerability exploitation, or malware propagation. If confirmed malicious, it could lead to command and control installation, data integrity damage, container escape, and further environment compromise.
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
- 10442d8b-0701-4c25-911d-d67b906e713c
- 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