A flaw was found in Diffusers, a library for pretrained diffusion models. A remote attacker could exploit this vulnerability by crafting a malicious Hub repository with custom Python pipeline code. The `DiffusionPipeline.from_pretrained` flow can bypass the `trust_remote_code` security mechanism, allowing the execution of arbitrary code on the system when a user interacts with the malicious repository. This could lead to high impact on confidentiality, integrity, and availability of the affected system.

Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, Diffusers' DiffusionPipeline.from_pretrained flow can bypass the trust_remote_code guard because download() validates model_index.json and custom pipeline code before later loading from a cached folder that can change, allowing a Hub repository with custom .py pipeline code to execute through the custom pipeline flow without passing custom_pipeline or trust_remote_code=True. This issue is fixed in version 0.38.0.

Diffusers is the a library for pretrained diffusion models. Prior to 0 ...

Diffusers: TOCTOU Trust Remote Code Bypass