Why LLMs Are Just the Tip of the AI Security Iceberg

This commentary outlines the evolving security risks posed by generative AI and LLMs—from hallucinations and data exposure to AI/ML supply-chain compromises—and argues that lack of visibility and controls raises enterprise risk. It recommends adopting a comprehensive AI security framework (MLSecOps) and five practical measures: implement risk management policies, use advanced vulnerability scanning and maintain an AI bill of materials (AIBOM), embrace open-source security tooling, and foster collaboration (e.g., bug bounty programs) to surface and mitigate hidden AI-related threats.