Detection: Kubernetes Nginx Ingress LFI

Description

The following analytic detects local file inclusion (LFI) attacks targeting Kubernetes Nginx ingress controllers. It leverages Kubernetes logs, parsing fields such as request and status to identify suspicious patterns indicative of LFI attempts. This activity is significant because LFI attacks can allow attackers to read sensitive files from the server, potentially exposing critical information. If confirmed malicious, this could lead to unauthorized access to sensitive data, further exploitation, and potential compromise of the Kubernetes environment.

 1`kubernetes_container_controller` 
 2| rex field=_raw "^(?<remote_addr>\S+)\s+-\s+-\s+\[(?<time_local>[^\]]*)\]\s\"(?<request>[^\"]*)\"\s(?<status>\S*)\s(?<body_bytes_sent>\S*)\s\"(?<http_referer>[^\"]*)\"\s\"(?<http_user_agent>[^\"]*)\"\s(?<request_length>\S*)\s(?<request_time>\S*)\s\[(?<proxy_upstream_name>[^\]]*)\]\s\[(?<proxy_alternative_upstream_name>[^\]]*)\]\s(?<upstream_addr>\S*)\s(?<upstream_response_length>\S*)\s(?<upstream_response_time>\S*)\s(?<upstream_status>\S*)\s(?<req_id>\S*)" 
 3| rename remote_addr AS src_ip, upstream_status as status, proxy_upstream_name as proxy 
 4| rex field=request "^(?<http_method>\S+)\s(?<url>\S+)\s" 
 5| eval phase="operate" 
 6| eval severity="high" 
 7| stats count min(_time) as firstTime max(_time) as lastTime by src_ip, status, url, http_method, host, http_user_agent, proxy, phase, severity, request 
 8| lookup local_file_inclusion_paths local_file_inclusion_paths AS request OUTPUT lfi_path 
 9| search lfi_path=yes 
10| `security_content_ctime(firstTime)` 
11| `security_content_ctime(lastTime)` 
12| `kubernetes_nginx_ingress_lfi_filter`

Data Source

Name Platform Sourcetype Source Supported App
N/A N/A N/A N/A N/A

Macros Used

Name Value
kubernetes_container_controller sourcetype=kube:container:controller
kubernetes_nginx_ingress_lfi_filter search *
kubernetes_nginx_ingress_lfi_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
ID Technique Tactic
T1212 Exploitation for Credential Access Credential Access
KillChainPhase.EXPLOITAITON
NistCategory.DE_CM
Cis18Value.CIS_13

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 Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

You must ingest Kubernetes logs through Splunk Connect for Kubernetes.

Known False Positives

unknown

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Local File Inclusion Attack detected on $host$ 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:controller
Integration ✅ Passing Dataset kubernetes kube:container:controller

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: 4