Researchers show that malicious changes can be embedded directly in a neural network’s weights and passed from one model to another through weight-space editing, effectively acting like model viruses. The finding highlights a new supply-chain risk for reused or fine-tuned models, since behavior and alignment can be altered without conventional data-level attacks.