Model backdoors are easy to create and hard to reliably remove
Summary
The article reports on experiments showing backdoors in open-weight coding models can persist through retraining and reinforcement learning, challenging assumptions that retraining cleans models. It introduces PersistBD and argues that verifiable training histories, transparency, and containment are needed to reduce backdoor risk in AI supply chains, especially for SMBs using open models.