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https://issues.apache.org/jira/browse/SPARK-60608?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ruifeng Zheng reassigned SPARK-60608:
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Assignee: Ruifeng Zheng
> Apply the class allowlist to nested model readers
> -------------------------------------------------
>
> Key: SPARK-60608
> URL: https://issues.apache.org/jira/browse/SPARK-60608
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 5.0.0
> Reporter: Ruifeng Zheng
> Assignee: Ruifeng Zheng
> Priority: Major
> Labels: pull-request-available
>
> Nested model readers should apply the same ML class-loading policy as
> top-level model loading in Spark Connect.
> DefaultParamsReader.loadParamsInstanceReader currently resolves the class
> recorded in nested model metadata directly. Route that resolution through
> MLAllowListedLoader, which is already used by default parameter loading.
> Add a separate MLClassLoadingSuite with checked-in model fixtures. A minimal
> RFormulaModel containing an allowlisted VectorAssembler should load
> successfully; the corresponding fixture naming an unregistered nested stage
> should fail with the allowlist error. The unregistered class is an inert
> placeholder with no executable payload.
> Pull request: https://github.com/apache/spark/pull/59854
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