splunk_escuAnomaly

Ollama Excessive API Requests

Detects high Ollama API request volumes from a single client in a short time window. A burst may indicate automated abuse or contribute to resource contention, but GIN access logs do not establish malicious intent or service impact; validate the client and workload against local usage baselines.

Detection Query

`ollama_server`
"[GIN]"

| rex field=_raw "\|\s+(?<raw_status>\d+)\s+\|\s+(?<raw_latency>[\d\.]+(?:µs|ms|s))\s+\|\s+(?<raw_src>[^|]+?)\s+\|\s+(?<raw_method>\w+)\s+\"(?<raw_path>[^\"]+)\""

| eval src=coalesce(src, trim(raw_src))
| eval uri_path=coalesce(uri_path, raw_path)
| eval http_method=coalesce(http_method, raw_method)
| eval http_response_code=coalesce(http_response_code, raw_status)
| eval response_time_ms=coalesce(response_time_ms, case(match(raw_latency, "µs$"), tonumber(replace(raw_latency, "µs", ""))/1000, match(raw_latency, "ms$"), tonumber(replace(raw_latency, "ms", "")), match(raw_latency, "s$"), tonumber(replace(raw_latency, "s", ""))*1000))

| where isnotnull(src)

| bin _time span=5m

| stats count as request_count
        dc(uri_path) as distinct_endpoints
        values(uri_path) as endpoints
  by _time src

| where request_count > 120

| eval severity="medium"

| eval attack_type="High Volume API Activity"

| `ollama_excessive_api_requests_filter`

Author

Rod Soto, Nasreddine Bencherchali, Splunk

Data Sources

Ollama Server

References

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

Raw Content

name: Ollama Excessive API Requests
id: 1cfab663-9adc-4169-a88c-6bae29ba3c70
version: 5
creation_date: '2025-10-13'
modification_date: '2026-10-09'
author: Rod Soto, Nasreddine Bencherchali, Splunk
status: production
type: Anomaly
description: Detects high Ollama API request volumes from a single client in a short time window. A burst may indicate automated abuse or contribute to resource contention, but GIN access logs do not establish malicious intent or service impact; validate the client and workload against local usage baselines.
data_source:
    - Ollama Server
search: |-
    `ollama_server`
    "[GIN]"

    | rex field=_raw "\|\s+(?<raw_status>\d+)\s+\|\s+(?<raw_latency>[\d\.]+(?:µs|ms|s))\s+\|\s+(?<raw_src>[^|]+?)\s+\|\s+(?<raw_method>\w+)\s+\"(?<raw_path>[^\"]+)\""

    | eval src=coalesce(src, trim(raw_src))
    | eval uri_path=coalesce(uri_path, raw_path)
    | eval http_method=coalesce(http_method, raw_method)
    | eval http_response_code=coalesce(http_response_code, raw_status)
    | eval response_time_ms=coalesce(response_time_ms, case(match(raw_latency, "µs$"), tonumber(replace(raw_latency, "µs", ""))/1000, match(raw_latency, "ms$"), tonumber(replace(raw_latency, "ms", "")), match(raw_latency, "s$"), tonumber(replace(raw_latency, "s", ""))*1000))

    | where isnotnull(src)

    | bin _time span=5m

    | stats count as request_count
            dc(uri_path) as distinct_endpoints
            values(uri_path) as endpoints
      by _time src

    | where request_count > 120

    | eval severity="medium"

    | eval attack_type="High Volume API Activity"

    | `ollama_excessive_api_requests_filter`
how_to_implement: |-
    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 automated services (CI/CD pipelines, monitoring tools, batch jobs), multiple users behind NAT/proxy infrastructure, or authorized load testing activities may trigger this detection during normal operations. Operator must adjust threshold accordingly.
references:
    - https://github.com/rosplk/ta-ollama
drilldown_searches:
    - name: View the detection results for - "$src$"
      search: |-
        %original_detection_search%
        | search src="$src$"
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$src$"
      search: |-
        from datamodel Risk.All_Risk
        | search normalized_risk_object IN ("$src$")
        | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object
        | `security_content_ctime(firstTime)`
        | `security_content_ctime(lastTime)`
      earliest_offset: 7d
      latest_offset: "0"
intermediate_findings:
    entities:
        - field: src
          type: system
          score: 20
          message: '[$request_count$] Ollama API requests from [$src$] across [$distinct_endpoints$] endpoints were observed in 5 minutes. Validate the client and workload before attributing the burst to abuse or service impact.'
analytic_story:
    - Suspicious Ollama Activities
asset_type: Web Application
mitre_attack_id:
    - T1498
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: application
security_domain: endpoint
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/ollama/server.log
          sourcetype: ollama:server
          source: server.log
      test_type: unit