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.
Attack Parameters
Attack Vector
Network
Can be exploited remotely
Attack Complexity
High
Difficult to exploit
Privileges Required
None
No privileges needed
User Interaction
Required
User action required
Impact Assessment
Confidentiality
High
Complete data leak
Integrity
High
Complete data modification
Availability
High
Complete denial of service
CVSS Vector v3.1
Weakness Type (CWE)
References 5
https://github.com/huggingface/diffusers/commit/a37f6f8394ac2a7ee8360c3abea811e…
security-advisories@github.com
https://github.com/huggingface/diffusers/issues/13446
security-advisories@github.com
https://github.com/huggingface/diffusers/pull/13448
security-advisories@github.com
https://github.com/huggingface/diffusers/releases/tag/v0.38.0
security-advisories@github.com
https://github.com/huggingface/diffusers/security/advisories/GHSA-7wx4-6vff-v64p
security-advisories@github.com