Evil models


"Platforms like Hugging Face host over a million models, ranging from state-of-the-art neural networks to poorly designed or maliciously altered versions. Amid this abundance lies a growing concern: model provenance.

"Imagine a widely used model, fine-tuned by a seemingly reputable maintainer, turning out to be a tool of a state actor. Subtle modifications in the training data set or architecture could embed biases, vulnerabilities or backdoors. These evil models could then be distributed as trusted resources, only to be weaponized later.

"This risk underscores the need for robust mechanisms to verify the origins and integrity of AI models. Initiatives like Sigstore, which employs tools such as SLSA (Supply chain Levels for Software Artifacts) to verify software provenance, must extend their efforts to encompass AI models and datasets. 

"Without such safeguards, the community remains vulnerable to manipulation at scale."


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