baseline_of_kubernetes_container_network_io_ratio.yml

name: Baseline Of Kubernetes Container Network IO Ratio
id: f395003b-6389-4e14-89bf-ac4dbea215bd
version: 2
date: '2024-09-24'
author: Matthew Moore, Splunk
type: Baseline
status: production
description: This baseline rule calculates the average ratio of inbound to outbound
  network IO for each Kubernetes container. It uses metrics from the Kubernetes API
  and the Splunk Infrastructure Monitoring Add-on. The rule generates a lookup table
  with the average and standard deviation of the network IO ratio for each container.
  This baseline can be used to detect anomalies in network communication behavior,
  which may indicate security threats such as data exfiltration, command and control
  communication, or compromised container behavior.
search: "| mstats avg(k8s.pod.network.io) as io where `kubernetes_metrics` by k8s.cluster.name
  k8s.pod.name k8s.node.name direction span=10s | eval service = replace('k8s.pod.name',
  \"-\\w{5}$|-[abcdef0-9]{8,10}-\\w{5}$\", \"\") | eval key = 'k8s.cluster.name' +
  \":\" + 'service' | stats avg(eval(if(direction=\"transmit\", io,null()))) as outbound_network_io
  avg(eval(if(direction=\"receive\", io,null()))) as inbound_network_io by key _time
  | eval inbound:outbound = inbound_network_io/outbound_network_io | eval outbound:inbound
  = outbound_network_io/inbound_network_io | stats avg(*:*) as avg_*:* stdev(*:*)
  as stdev_*:* count latest(_time) as last_seen by key | outputlookup k8s_container_network_io_ratio_baseline"
how_to_implement: "To implement this detection, follow these steps: 1. Deploy the
  OpenTelemetry Collector (OTEL) to your Kubernetes cluster. 2. Enable the hostmetrics/process
  receiver in the OTEL configuration. 3. Ensure that the process metrics, specifically
  Process.cpu.utilization and process.memory.utilization, are enabled. 4. Install
  the Splunk Infrastructure Monitoring (SIM) add-on. (ref: https://splunkbase.splunk.com/app/5247)
  5. Configure the SIM add-on with your Observability Cloud Organization ID and Access
  Token. 6. Set up the SIM modular input to ingest Process Metrics. Name this input
  \"sim_process_metrics_to_metrics_index\". 7. In the SIM configuration, set the Organization
  ID to your Observability Cloud Organization ID. 8. 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') 9. Set the Metric Resolution to 10000.
  10. Leave all other settings at their default values."
known_false_positives: none
references: []
tags:
  analytic_story:
  - Abnormal Kubernetes Behavior using Splunk Infrastructure Monitoring
  detections:
  - Kubernetes Anomalous Inbound to Outbound Network IO Ratio
  product:
  - Splunk Enterprise
  - Splunk Enterprise Security
  - Splunk Cloud
  security_domain: network
deployment:
  scheduling:
    cron_schedule: 0 2 * * 0
    earliest_time: -30d@d
    latest_time: -1d@d
    schedule_window: auto