Browse Rules

Azure OpenAI Insecure Output Handling

Detects when Azure OpenAI requests result in zero response length, potentially indicating issues in output handling that might lead to security exploits such as data leaks or code execution. This can occur in cases where the API fails to handle outputs correctly under certain input conditions.

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.

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 degradation or service disruption, such as large input sizes or rapid API calls.