| Package | Affected versions | Patched versions |
|---|---|---|
| diffusers | < 0.38.0 | 0.38.0 |
| diffusers | < 0.38.0 | 0.38.0 |
A trust_remote_code bypass in DiffusionPipeline.from_pretrained allows arbitrary remote code execution despite the user passing trust_remote_code=False (or omitting it, which is the default). The vulnerability has three variants, all sharing the same root cause — the trust_remote_code gate was implemented inside DiffusionPipeline.download() rather than at the actual dynamic-module load site, so any code path that bypassed or short-circuited download() also bypassed the security check:
custom_pipeline. DiffusionPipeline.from_pretrained('repoA', custom_pipeline='attacker/repoB', trust_remote_code=False) — the gate evaluated against repoA's file list rather than repoB's, so repoB's pipeline.py was loaded and executed.custom_pipeline. DiffusionPipeline.from_pretrained('/local/snapshot', custom_pipeline='attacker/repoB', trust_remote_code=False) — the local-path branch never invoked download(), so the gate was never reached and remote code from repoB executed.DiffusionPipeline.from_pretrained('/local/snapshot', trust_remote_code=False)unet/my_unet_model.pymodel_index.jsondownload()Silent remote code execution on the victim's machine. Anyone calling DiffusionPipeline.from_pretrained with custom pipelines is impacted.
Yes. Fixed in diffusers 0.38.0 via PR #13448. All users on versions < 0.38.0 should upgrade:
pip install --upgrade "diffusers>=0.38.0"
The fix moves the trust_remote_code gate out of DiffusionPipeline.download() and into get_cached_module_file in src/diffusers/utils/dynamic_modules_utils.py, which is the actual chokepoint for every dynamic module load (local, Hub, or community mirror). All three variants now raise ValueError instead of executing untrusted code.
If upgrading immediately is not possible:
from_pretrained with pretrained_model_name_or_path, custom_pipeline, and local snapshot directories from fully trusted sources that have been audited.custom_pipeline= pointing at a Hub repository different from the primary pretrained_model_name_or_path before reading its pipeline.py.from_pretrained on a local snapshot, inspect the snapshot for unexpected *.py files, especially under component subdirectories (unet/, scheduler/, etc.) and at the snapshot root.These are mitigations, not fixes — the only complete remediation is upgrading to 0.38.0.
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