Amazon EKS Kubernetes cluster scan detection
THIS IS A EXPERIMENTAL DETECTION
This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.
Description
This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS
- Type: Hunting
-
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2020-04-15
- Author: Rod Soto, Splunk
- ID: 294c4686-63dd-4fe6-93a2-ca807626704a
Annotations
Kill Chain Phase
- Exploitation
NIST
- DE.AE
CIS20
- CIS 10
CVE
Search
1
2
3
4
5
6
`aws_cloudwatchlogs_eks` "user.username"="system:anonymous" userAgent!="AWS Security Scanner"
| rename sourceIPs{} as src_ip
| stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{}
| `security_content_ctime(lastTime)`
| `security_content_ctime(firstTime)`
|`amazon_eks_kubernetes_cluster_scan_detection_filter`
Macros
The SPL above uses the following Macros:
amazon_eks_kubernetes_cluster_scan_detection_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- user.username
- userAgent
- sourceIPs{}
- responseStatus.reason
- source
- responseStatus.code
- verb
- requestURI
- src_ip
- user.groups{}
How To Implement
You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudWatch EKS Logs inputs.
Known False Positives
Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | tbd |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Reference
Test Dataset
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 | version: 1