AI Model Security adds support for scanning two new model sources.
AI Model Security now supports JFrog Artifactory and GitLab Model
Registry as sources, adding to existing support for Local Storage,
HuggingFace, S3, GCS, and Azure Blob Storage.
You can now
scan models stored in two new cloud
storage types:
- Artifactory—Models stored in JFrog Artifactory ML Model, Hugging Face, or
generic artifact repositories.
- GitLab Model Registry—Models stored in the GitLab Model Registry.
Organizations can now establish consistent security standards across models
regardless of where development teams store them. Security Groups can enforce the
same comprehensive validation (deserialization threats, neural backdoors, license
compliance, insecure formats) for models in Artifactory and GitLab that you already
apply to other Sources.
This expansion reduces operational risk from unvalidated models by eliminating blind
spots in your AI security posture. Teams no longer need to move models between
repositories to apply security rules or generate compliance audit trails.
Configure Artifactory and GitLab sources through the same
Security Group workflows used for other
model repositories.
