MLflow 2.9.2 is a patch release, containing several critical security fixes and configuration updates to support extremely large model artifacts.
Features:
[Deployments] Add the mlflow.deployments.openai API to simplify direct access to OpenAI services through the deployments API (#10473, @prithvikannan)
[Server-infra] Add a new environment variable that permits disabling http redirects within the Tracking Server for enhanced security in publicly accessible tracking server deployments (#10673, @daniellok-db)
[Artifacts] Add environment variable configurations for both Multi-part upload and Multi-part download that permits modifying the per-chunk size to support extremely large model artifacts (#10648, @harupy)
Security fixes:
[Server-infra] Disable the ability to inject malicious code via manipulated YAML files by forcing YAML rendering to be performed in a secure Sandboxed mode (#10676, @BenWilson2, #10640, @harupy)
[Artifacts] Prevent path traversal attacks when querying artifact URI locations by disallowing .. path traversal queries (#10653, @B-Step62)
[Data] Prevent a mechanism for conducting a malicious file traversal attack on Windows when using tracking APIs that interface with HTTPDatasetSource (#10647, @BenWilson2)
[Artifacts] Prevent a potential path traversal attack vector via encoded url traversal paths by decoding paths prior to evaluation (#10650, @B-Step62)
[Artifacts] Prevent the ability to conduct path traversal attacks by enforcing the use of sanitized paths with the tracking server (#10666, @harupy)
[Artifacts] Prevent path traversal attacks when using an FTP server as a backend store by enforcing base path declarations prior to accessing user-supplied paths (#10657, @harupy)
Documentation updates:
[Docs] Add an end-to-end tutorial for RAG creation and evaluation (#10661, @AbeOmor)
MLflow 2.9.2 is a patch release, containing several critical security fixes and configuration updates to support extremely large model artifacts.
Features:
[Deployments] Add the mlflow.deployments.openai API to simplify direct access to OpenAI services through the deployments API (#10473, @prithvikannan)
[Server-infra] Add a new environment variable that permits disabling http redirects within the Tracking Server for enhanced security in publicly accessible tracking server deployments (#10673, @daniellok-db)
[Artifacts] Add environment variable configurations for both Multi-part upload and Multi-part download that permits modifying the per-chunk size to support extremely large model artifacts (#10648, @harupy)
Security fixes:
[Server-infra] Disable the ability to inject malicious code via manipulated YAML files by forcing YAML rendering to be performed in a secure Sandboxed mode (#10676, @BenWilson2, #10640, @harupy)
[Artifacts] Prevent path traversal attacks when querying artifact URI locations by disallowing .. path traversal queries (#10653, @B-Step62)
[Data] Prevent a mechanism for conducting a malicious file traversal attack on Windows when using tracking APIs that interface with HTTPDatasetSource (#10647, @BenWilson2)
[Artifacts] Prevent a potential path traversal attack vector via encoded url traversal paths by decoding paths prior to evaluation (#10650, @B-Step62)
[Artifacts] Prevent the ability to conduct path traversal attacks by enforcing the use of sanitized paths with the tracking server (#10666, @harupy)
[Artifacts] Prevent path traversal attacks when using an FTP server as a backend store by enforcing base path declarations prior to accessing user-supplied paths (#10657, @harupy)
Documentation updates:
[Docs] Add an end-to-end tutorial for RAG creation and evaluation (#10661, @AbeOmor)
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Bumps mlflow from 2.9.0 to 2.9.2.
Release notes
Sourced from mlflow's releases.
Changelog
Sourced from mlflow's changelog.
Commits
6ca7246Runpython3 dev/update_mlflow_versions.py pre-release ...(#10679)27a3b24Createmlflow.deployments.openai(#10473)7f2a686Fix ImportError in new langchain version (#10677)60e209eAdd env var to disable redirects again (#10673)0cd7b26Adding Notebook for RAG Blog (#10661)8ef0659Use validated path after path validation (#10666)8029113Add sandboxed jinja2 loader for yaml rendering (#10676)81deca5Add Tensorflow landing page (#10646)46910c2Make MPU / MPD chunk size configurable via environment variables (#10648)f00bd70Applyos.path.basenamebefore.or..check inFTPArtifactRepository...Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting
@dependabot rebase.Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot show