As frontier artificial intelligence (AI) models--that is, models that match or exceed the capabilities of the most advanced models at the time of their development--become more capable, protecting them from theft and misuse will become more important. The authors of this report explore what it would take to protect model weights--the learnable parameters that encode the core intelligence of an AI--from theft by a variety of potential attackers.