So Many AI Security Benchmarks, But None Tell the Whole Story

Measuring the security of AI models is a complex task. A variety of benchmarks are being developed to assess different aspects of AI model security. However, these benchmarks have limitations and do not provide a complete picture. As a result, testing AI models against an organization's own code and workflows is still necessary to ensure their security. The current benchmarks only target specific variables, leaving gaps in the overall security assessment. They are not a replacement for customized testing.