Detection: Ollama Possible API Endpoint Scan Reconnaissance

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.

Updated Date: 2025-10-05 ID: ad3f352a-0347-48ee-86b9-670b5025a548 Author: Rod Soto Type: Anomaly Product: Splunk Enterprise Security

Description

Detects API reconnaissance and endpoint scanning activity against Ollama servers by identifying sources probing multiple API endpoints within short timeframes, particularly when using HEAD requests or accessing diverse endpoint paths, which indicates systematic enumeration to map the API surface, discover hidden endpoints, or identify vulnerabilities before launching targeted attacks.

Search

1`ollama_server` "[GIN]" 
2| bin _time span=5m 
3| stats count as total_requests, values(dest) as dest, values(http_method) as methods, values(status) as status_codes by _time, src, host 
4| where total_requests > 120 
5| eval severity="medium" 
6| eval attack_type="API Activity Surge" 
7| stats count by _time, host, src, total_requests, dest, methods, status_codes, severity, attack_type 
8| `ollama_possible_api_endpoint_scan_reconnaissance_filter`

Data Source

Name	Platform	Sourcetype	Source
Ollama Server	N/A	`'ollama:server'`	`'server.log'`

Macros Used

Name	Value
ollama_server	`(sourcetype="ollama:server")`
ollama_possible_api_endpoint_scan_reconnaissance_filter	`search *`

ollama_possible_api_endpoint_scan_reconnaissance_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
T1595	Active Scanning	Reconnaissance

Reconnaissance

DE.AE

CIS 10

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

Ingest Ollama logs via Splunk TA-ollama add-on by configuring file monitoring inputs pointed to your Ollama server log directories (sourcetype: ollama:server), or enable HTTP Event Collector (HEC) for real-time API telemetry and prompt analytics (sourcetypes: ollama:api, ollama:prompts). CIM compatibility using the Web datamodel for standardized security detections.

Known False Positives

Legitimate web application clients or mobile apps that access multiple API endpoints as part of normal functionality, monitoring and health check systems probing various endpoints for availability, load balancers performing health checks across different paths, API testing frameworks during development and QA processes, or users navigating through web interfaces that trigger multiple API calls may generate similar patterns during normal operations.

Associated Analytic Story

Suspicious Ollama Activities

Risk Based Analytics (RBA)

Risk Message:

API reconnaissance activity detected from $src$ on $host$ with $total_requests$ requests across different endpoints using methods $methods$ and receiving status codes $status_codes$, indicating systematic endpoint enumeration to map API attack surface and identify potential vulnerabilities.

Risk Object	Risk Object Type	Risk Score	Threat Objects
src	system	10	No Threat Objects

References

https://github.com/rosplk/ta-ollama

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	Not Applicable	N/A	N/A	N/A
Unit	✅ Passing	Dataset	`server.log`	`ollama:server`
Integration	✅ Passing	Dataset	`server.log`	`ollama:server`

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: 1