| ID | Technique | Tactic |
|---|---|---|
| T1204 | User Execution | Execution |
Detection: Kubernetes Falco Shell Spawned
Description
The following analytic detects instances where a shell is spawned within a Kubernetes container. Leveraging Falco, a cloud-native runtime security tool, this analytic monitors system calls within the Kubernetes environment and flags when a shell is spawned. This activity is significant for a SOC as it may indicate unauthorized access, allowing an attacker to execute arbitrary commands, manipulate container processes, or escalate privileges. If confirmed malicious, this could lead to data breaches, service disruptions, or unauthorized access to sensitive information, severely impacting the Kubernetes infrastructure's integrity and security.
Search
1`kube_container_falco` "A shell was spawned in a container"
2| fillnull
3| stats count by container_image container_image_tag container_name parent proc_exepath process user
4| `kubernetes_falco_shell_spawned_filter`
Data Source
| Name | Platform | Sourcetype | Source |
|---|---|---|---|
| Kubernetes Falco |  Kubernetes |
'kube:container:falco' |
'kubernetes' |
Macros Used
| Name | Value |
|---|---|
| kube_container_falco | sourcetype="kube:container:falco" |
| kubernetes_falco_shell_spawned_filter | search * |
kubernetes_falco_shell_spawned_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
MITRE ATT&CK
Kill Chain Phases
NIST
CIS
Threat Actors
KillChainPhase.INSTALLATION
NistCategory.DE_AE
Cis18Value.CIS_13
LAPSUS$
Scattered Spider
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 |
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.
Implementation
The detection is based on data that originates from Kubernetes Audit logs. Ensure that audit logging is enabled in your Kubernetes cluster. Kubernetes audit logs provide a record of the requests made to the Kubernetes API server, which is crucial for monitoring and detecting suspicious activities. Configure the audit policy in Kubernetes to determine what kind of activities are logged. This is done by creating an Audit Policy and providing it to the API server. Use the Splunk OpenTelemetry Collector for Kubernetes to collect the logs. This doc will describe how to collect the audit log file https://github.com/signalfx/splunk-otel-collector-chart/blob/main/docs/migration-from-sck.md. When you want to use this detection with AWS EKS, you need to enable EKS control plane logging https://docs.aws.amazon.com/eks/latest/userguide/control-plane-logs.html. Then you can collect the logs from Cloudwatch using the AWS TA https://splunk.github.io/splunk-add-on-for-amazon-web-services/CloudWatchLogs/.
Known False Positives
unknown
Associated Analytic Story
Risk Based Analytics (RBA)
| Risk Message | Risk Score | Impact | Confidence |
|---|---|---|---|
| A shell is spawned in the container $container_name$ by user $user$. | 49 | 70 | 70 |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
References
Detection Testing
| Test Type | Status | Dataset | Source | Sourcetype |
|---|---|---|---|---|
| Validation | ✅ Passing | N/A | N/A | N/A |
| Unit | ✅ Passing | Dataset | kubernetes |
kube:container:falco |
| Integration | ✅ Passing | Dataset | kubernetes |
kube:container:falco |
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: 3