v3.12.0

New Features

• SageMaker Token Generator (#5868): Embed the aws-sagemaker-token-generator library into sagemaker.core so users can generate SageMaker bearer tokens without installing a separate wheel. Usage: from sagemaker.core.aws_sagemaker_token_generator import provide_token
• Feature Processor - Spark 3.5 / Python 3.12 support (#5816): Dynamic Spark image resolution based on installed PySpark and Python versions. Supports Spark 3.1/3.2/3.3/3.5 with Python 3.9 and 3.12. Auto-installs sagemaker-feature-store-pyspark for Spark remote jobs.

Bug Fixes

• Networking vpc_config AttributeError and telemetry region fallback (#5839): Fix AttributeError on vpc_config in networking and telemetry region fallback for classmethods.
• Add CustomAttributes field to DefaultPayloadsModel (#5870): Add missing CustomAttributes field to DefaultPayloadsModel.
• sagemaker-core: Preserve falsy values in serialize() output (#5860): Fix bug where False, 0, and "" were silently dropped by serialize() due to truthy check. This caused issues like optimize_model=False being sent as True.
• serve: Prevent code injection in capture_dependencies path interpolation (#5792): Security fix — use repr() escaping to prevent code injection via crafted directory names in ModelBuilder with dependencies={"auto": True}. (CWE-94, P414309851)
• VolumeSizeInGB missing from v3 deploy for JumpStart models (#5847): Fix VolumeSizeInGB not being passed through when deploying models with inference_volume_size from JumpStart config.