Potential Denial of Azure OpenAI ML Service
Detects patterns indicative of Denial-of-Service (DoS) attacks on machine learning (ML) models, focusing on unusually high volume and frequency of requests or patterns of requests that are known to cause performance…
Description
Detects patterns indicative of Denial-of-Service (DoS) attacks on machine learning (ML) models, focusing on unusually high volume and frequency of requests or patterns of requests that are known to cause performance degradation or service disruption, such as large input sizes or rapid API calls.
Detection logic
Its licence does not clear it for publishing here
Sunturai publishes a detection's own text where the licence it arrived under has been reviewed and permits it, and Elastic License 2.0 has not. The query as its source wrote it, its canonical form and the hash that pins this revision are in the workspace record.
Known benign triggers
- Legitimate spikes in usage due to business processes
- Unexpected system errors
MITRE ATT&CK mappings
Not mapped to ATT&CK.
References
| Reference | Cited by |
|---|---|
| atlas.mitre.org/techniques/AML.T0029 | Only this detection cites it |
| genai.owasp.org/llmrisk/llm04-model-denial-of-service | Only this detection cites it |
From the source
- At source
- Open at source
- Upstream identifier
- b0450411-46e5-46d2-9b35-8b5dd9ba763e
- Tagged by the source as
- Data Source: Azure Event HubsData Source: Azure OpenAIDomain: LLMMitre Atlas: T0029Resources: Investigation GuideUse Case: Denial of Service
Licence
- Published under
- Elastic License 2.0Read the licence
- Attribution
- Required
Authorship
- Written by
- Published
- Aug 27, 2026
- Version
- 1