Description
As organizations deploy AI models through APIs, they face unique security challenges that go beyond traditional application security. AI APIs not only need protection against common web vulnerabilities but also require safeguards against model-specific attacks, data poisoning, and inference manipulation.
The sensitive nature of AI models and their training data, combined with their potential impact on business decisions, makes security a critical concern. Here is a framework for implementing robust security measures for AI APIs in production environments, covering everything from authentication to model-specific protections.
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