ID | Technique | Tactic |
---|---|---|
T1204 | User Execution | Execution |
Detection: Kubernetes newly seen TCP edge
EXPERIMENTAL DETECTION
This detection status is set to experimental. The Splunk Threat Research team has not yet fully tested, simulated, or built comprehensive datasets for this detection. As such, this analytic is not officially supported. If you have any questions or concerns, please reach out to us at research@splunk.com.
Description
The following analytic identifies newly seen TCP communication between source and destination workload pairs within a Kubernetes cluster. It leverages Network Performance Monitoring metrics collected via an OTEL collector and pulled from Splunk Observability Cloud. The detection compares network activity over the last hour with the past 30 days to spot new inter-workload communications. This is significant as new connections can indicate changes in application behavior or potential security threats. If malicious, unauthorized connections could lead to data breaches, privilege escalation, lateral movement, or disruption of critical services, compromising the application's integrity, availability, and confidentiality.
Search
1
2| mstats count(tcp.packets) as tcp.packets_count where `kubernetes_metrics` AND earliest=-1h by k8s.cluster.name source.workload.name dest.workload.name
3| eval current="True"
4| append [ mstats count(tcp.packets) as tcp.packets_count where `kubernetes_metrics` AND earliest=-30d latest=-1h by source.workload.name dest.workload.name
5| eval current="false" ]
6| eventstats values(current) as current by source.workload.name dest.workload.name
7| search current="true" current!="false"
8| rename k8s.cluster.name as host
9| `kubernetes_newly_seen_tcp_edge_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
N/A | N/A | N/A | N/A | N/A |
Macros Used
Name | Value |
---|---|
kubernetes_metrics | index=kubernetes_metrics |
kubernetes_newly_seen_tcp_edge_filter | search * |
kubernetes_newly_seen_tcp_edge_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
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 |
Implementation
To gather NPM metrics the Open Telemetry to the Kubernetes Cluster and enable Network Performance Monitoring according to instructions found in Splunk Docs https://docs.splunk.com/observability/en/infrastructure/network-explorer/network-explorer-setup.html#network-explorer-setup In order to access those metrics from within Splunk Enterprise and ES, the Splunk Infrastructure Monitoring add-on must be installed and configured on a Splunk Search Head. Once installed, first configure the add-on with your O11y Cloud Org ID and Access Token. Lastly set up the add-on to ingest metrics from O11y cloud using the following settings, and any other settings left at default:
- Name sim_npm_metrics_to_metrics_index
- Metric Resolution 10000
Known False Positives
unknown
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
Kubernetes newly seen TCP edge in kubernetes cluster $host$ | 25 | 50 | 50 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | Not Applicable | N/A | N/A | N/A |
Unit | ❌ Failing | N/A | N/A |
N/A |
Integration | ❌ Failing | N/A | N/A |
N/A |
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