Mapping the AI attack surface: Vulnerabilities in the model lifecycle

Red Hat identifies multiple attack vectors against AI systems throughout their development lifecycle, including backdoor triggers that cause targeted failures, model theft through API queries, and privacy attacks that reveal training data. The article highlights how standard security benchmarks miss many real-world vulnerabilities that could compromise AI models in production.