Detection rules › Splunk

Kubernetes Shell Running on Worker Node with CPU Activity

Status
experimental
Severity
low
Group by
"host.name", "k8s.cluster.name", "k8s.node.name", "process.executable.name", "process.pid"
Author
Matthew Moore, Splunk
Source
github.com/splunk/security_content

The following analytic identifies shell activity within the Kubernetes privilege scope on a worker node, specifically when shell processes are consuming CPU resources. It leverages process metrics from an OTEL collector hostmetrics receiver, pulled from Splunk Observability Cloud via the Splunk Infrastructure Monitoring Add-on, focusing on process.cpu.utilization and process.memory.utilization. This activity is significant as unauthorized shell processes can indicate a security threat, potentially compromising the node and the entire Kubernetes cluster. If confirmed malicious, attackers could gain full control over the host's resources, leading to data theft, service disruption, privilege escalation, and further attacks within the cluster.

MITRE ATT&CK coverage

TacticTechniques
ExecutionT1204 User Execution

Rule body splunk

name: Kubernetes Shell Running on Worker Node with CPU Activity
id: cc1448e3-cc7a-4518-bc9f-2fa48f61a22b
version: 10
creation_date: '2024-01-10'
modification_date: '2026-05-13'
author: Matthew Moore, Splunk
status: experimental
type: Anomaly
description: The following analytic identifies shell activity within the Kubernetes privilege scope on a worker node, specifically when shell processes are consuming CPU resources. It leverages process metrics from an OTEL collector hostmetrics receiver, pulled from Splunk Observability Cloud via the Splunk Infrastructure Monitoring Add-on, focusing on process.cpu.utilization and process.memory.utilization. This activity is significant as unauthorized shell processes can indicate a security threat, potentially compromising the node and the entire Kubernetes cluster. If confirmed malicious, attackers could gain full control over the host's resources, leading to data theft, service disruption, privilege escalation, and further attacks within the cluster.
data_source: []
search: |-
    | mstats avg(process.cpu.utilization) as process.cpu.utilization avg(process.memory.utilization) as process.memory.utilization where `kubernetes_metrics` AND process.executable.name IN ("sh","bash","csh", "tcsh") by host.name k8s.cluster.name k8s.node.name process.pid process.executable.name span=10s
    | search process.cpu.utilization>0
    | stats avg(process.cpu.utilization) as process.cpu.utilization avg(process.memory.utilization) as process.memory.utilization
      BY host.name k8s.cluster.name k8s.node.name
         process.pid process.executable.name
    | rename host.name as host
    | `kubernetes_shell_running_on_worker_node_with_cpu_activity_filter`
how_to_implement: "To implement this detection, follow these steps:\n* Deploy the OpenTelemetry Collector (OTEL) to your Kubernetes cluster.\n* Enable the hostmetrics/process receiver in the OTEL configuration.\n* Ensure that the process metrics, specifically Process.cpu.utilization and process.memory.utilization, are enabled.\n* Install the Splunk Infrastructure Monitoring (SIM) add-on. (ref: https://splunkbase.splunk.com/app/5247)\n * Configure the SIM add-on with your Observability Cloud Organization ID and Access Token.\n* Set up the SIM modular input to ingest Process Metrics. Name this input \"sim_process_metrics_to_metrics_index\".\n* In the SIM configuration, set the Organization ID to your Observability Cloud Organization ID.\n* Set the Signal Flow Program to the following: data('process.threads').publish(label='A'); data('process.cpu.utilization').publish(label='B'); data('process.cpu.time').publish(label='C'); data('process.disk.io').publish(label='D'); data('process.memory.usage').publish(label='E'); data('process.memory.virtual').publish(label='F'); data('process.memory.utilization').publish(label='G'); data('process.cpu.utilization').publish(label='H'); data('process.disk.operations').publish(label='I'); data('process.handles').publish(label='J'); data('process.threads').publish(label='K')\n* Set the Metric Resolution to 10000.\n * Leave all other settings at their default values.\n* Run the Search Baseline Of Kubernetes Container Network IO Ratio"
known_false_positives: No false positives have been identified at this time.
references:
    - https://github.com/signalfx/splunk-otel-collector-chart/tree/main
intermediate_findings:
    entities:
        - field: host
          type: system
          score: 20
          message: Kubernetes shell with cpu activity running on worker node on host $host$
analytic_story:
    - Abnormal Kubernetes Behavior using Splunk Infrastructure Monitoring
asset_type: Kubernetes
mitre_attack_id:
    - T1204
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: cloud
security_domain: network

Stages and Predicates

Stage 1: search

| mstats avg(process.cpu.utilization) as process.cpu.utilization avg(process.memory.utilization) as process.memory.utilization where `kubernetes_metrics` AND process.executable.name IN ("sh","bash","csh", "tcsh") by host.name k8s.cluster.name k8s.node.name process.pid process.executable.name span=10s

Stage 2: search

| search process.cpu.utilization>0

Stage 3: stats

| stats avg(process.cpu.utilization) as process.cpu.utilization avg(process.memory.utilization) as process.memory.utilization
  BY host.name k8s.cluster.name k8s.node.name
     process.pid process.executable.name

Stage 4: rename

| rename host.name as host

Stage 5: search

| `kubernetes_shell_running_on_worker_node_with_cpu_activity_filter`

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.

FieldKindValues
process.cpu.utilizationgt
  • 0
process.executable.namein
  • "bash"
  • "csh"
  • "sh"
  • "tcsh"
spaneq
  • 10s

Search terms

Bare-string tokens in the SPL search body. Splunk matches each token against _raw (the untyped raw event text) anywhere it appears, not against a specific field. These don't surface in the Indicators table because they aren't predicates on a known field.

StageTerm
1mstats
1avg
1process.cpu.utilization
1as
1process.cpu.utilization
1avg
1process.memory.utilization
1as
1process.memory.utilization
1where
1by
1process.executable.name
1host.name
1k8s.cluster.name
1k8s.node.name
1process.pid