This paper introduces ShieldCLIP, a framework for selective safety alignment in multimodal foundation models like CLIP. It conditions safety alignment on the observed safety state of each modality, preserving safe content and redirecting only unsafe content. The authors also introduce ViSUv2, a 195k-quadruplet dataset with independent per-modality safety labels. ShieldCLIP achieves consistent reductions in harmful outputs in various tasks and settings.