Multimodal systems are transforming AI by enabling models to understand and act across language, vision, and other modalities, driving advances in robotics, autonomous driving, and scientific discovery. However, these capabilities raise serious safety and trustworthiness concerns, as traditional safeguards often fall short in multimodal contexts. The Workshop on Safe and Trustworthy Multimodal AI Systems (SaFeMM-AI) at ICCV 2025 brings together the computer vision community to address challenges including hallucinations, privacy leakage, and jailbreak vulnerabilities, and to promote the development of safer, more robust, and reliable multimodal models that can handle unsafe or adversarial inputs and consistently produce trustworthy outputs.