Ollama Suspicious Prompt Injection Jailbreak

name: Ollama Suspicious Prompt Injection Jailbreak
id: aac5df6f-9151-4da6-bdb2-5691aa6e376f
version: 2
date: '2026-03-10'
author: Rod Soto
status: experimental
type: Anomaly
description: Detects potential prompt injection or jailbreak attempts against Ollama API endpoints by identifying requests with abnormally long response times. Attackers often craft complex, layered prompts designed to bypass AI safety controls, which typically result in extended processing times as the model attempts to parse and respond to these malicious inputs. This detection monitors /api/generate and /api/chat endpoints for requests exceeding 30 seconds, which may indicate sophisticated jailbreak techniques, multi-stage prompt injections, or attempts to extract sensitive information from the model.
data_source:
    - Ollama Server
search: '`ollama_server` "GIN" ("*/api/generate*" OR "*/v1/chat/completions*") | rex field=_raw "\|\s+(?<status_code>\d+)\s+\|\s+(?<response_time>[\d\.]+[a-z]+)\s+\|\s+(?<src_ip>[\:\da-f\.]+)\s+\|\s+(?<http_method>\w+)\s+\"(?<uri_path>[^\"]+)\"" | rex field=response_time "^(?:(?<minutes>\d+)m)?(?<seconds>[\d\.]+)s$" | eval response_time_seconds=if(isnotnull(minutes), tonumber(minutes)*60+tonumber(seconds), tonumber(seconds)) | eval src=src_ip | where response_time_seconds > 30 | bin _time span=10m | stats count as long_request_count, avg(response_time_seconds) as avg_response_time, max(response_time_seconds) as max_response_time, values(uri_path) as uri_path, values(status_code) as status_codes by _time, src, host | where long_request_count > 170 | eval avg_response_time=round(avg_response_time, 2) | eval max_response_time=round(max_response_time, 2) | eval severity=case( long_request_count > 50 OR max_response_time > 55, "critical", long_request_count > 20 OR max_response_time > 40, "high", 1=1, "medium" ) | eval attack_type="Potential Prompt Injection / Jailbreak" | table _time, host, src, uri_path, long_request_count, avg_response_time, max_response_time, status_codes, severity, attack_type | `ollama_suspicious_prompt_injection_jailbreak_filter`'
how_to_implement: 'Ingest Ollama logs via Splunk TA-ollama add-on by configuring file monitoring inputs pointed to your Ollama server log directories (sourcetype: ollama:server), or enable HTTP Event Collector (HEC) for real-time API telemetry and prompt analytics (sourcetypes: ollama:api, ollama:prompts). CIM compatibility using the Web datamodel for standardized security detections.'
known_false_positives: Legitimate complex queries requiring extensive model reasoning, large context windows processing substantial amounts of text, batch processing operations, or resource-constrained systems experiencing performance degradation may trigger this detection during normal operations.
references:
    - https://github.com/rosplk/ta-ollama
    - https://github.com/OWASP/www-project-ai-testing-guide
drilldown_searches:
    - name: View the detection results for - "$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 ("$src$") starthoursago=168 | 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: $info_min_time$
      latest_offset: $info_max_time$
rba:
    message: Potential prompt injection or jailbreak attempt detected from $src$ with $long_request_count$ requests averaging $avg_response_time$ seconds, indicating possible attempts to bypass AI safety controls or extract sensitive information from the Ollama model.
    risk_objects:
        - field: src
          type: system
          score: 20
    threat_objects: []
tags:
    analytic_story:
        - Suspicious Ollama Activities
    asset_type: Web Application
    mitre_attack_id:
        - T1190
        - T1059
    product:
        - Splunk Enterprise
        - Splunk Enterprise Security
        - Splunk Cloud
    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