Potential Azure OpenAI Model Theft

Monitors for suspicious activities that may indicate theft or unauthorized duplication of machine learning (ML) models, such as unauthorized API calls, atypical access patterns, or large data transfers that are unusual during model interactions.

Rule type: esql

Rule indices: None

Severity: medium

Risk score: 47

Runs every: 10m

Searches indices from: now-60m (Date Math format, see also Additional look-back time)

Maximum alerts per execution: 100

References:

Tags:

Domain: LLM
Data Source: Azure OpenAI
Data Source: Azure Event Hubs
Use Case: Model Theft
Mitre Atlas: T0044

Version: 1

Rule authors:

Elastic

Rule license: Elastic License v2

Setup

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Setup

For more information on streaming events, see the Azure OpenAI documentation:

https://learn.microsoft.com/en-us/azure/azure-monitor/essentials/stream-monitoring-data-event-hubs

Rule query

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from logs-azure_openai.logs-*
| where azure.open_ai.operation_name == "ListKey" and azure.open_ai.category == "Audit"
| KEEP @timestamp, azure.open_ai.operation_name , azure.open_ai.category, azure.resource.group, azure.resource.name, azure.open_ai.properties.response_length
| stats count = count(), max_data_transferred = max(azure.open_ai.properties.response_length) by azure.resource.group , azure.resource.name
| where count >= 100 or max_data_transferred >= 1000000
| sort count desc

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