AI model poisoning is a stealthy cyber threat where adversaries manipulate training data or models to introduce hidden vulnerabilities or biases, compromising the integrity of AI systems in production. This silent saboteur can lead to catastrophic failures, biased decisions, or even malicious behaviors in critical applications like healthcare, finance, and autonomous vehicles. Discover how AI model poisoning infiltrates your supply chain, the latest attack vectors, and actionable defense strategies to fortify your AI pipeline against this invisible menace.