[Snyk] Fix for 4 vulnerabilities

[q1blue]

Snyk has created this PR to fix 4 vulnerabilities in the pip dependencies of this project.

Snyk changed the following file(s):

• responsibleai_vision/requirements-automl.txt

⚠️ Warning

statsmodels 0.13.5 requires scipy, which is not installed.
statsmodels 0.13.5 requires scipy, which is not installed.
sklearn-pandas 1.7.0 requires scipy, which is not installed.
shap 0.42.1 requires scipy, which is not installed.
scikit-learn 1.0.2 requires scipy, which is not installed.
saliency 0.1.3 requires scikit-image, which is not installed.
resnest 0.0.6b20210504 requires scipy, which is not installed.
raiutils 0.4.2 requires scipy, which is not installed.
pyOpenSSL 24.3.0 has requirement cryptography<45,>=41.0.5, but you have cryptography 45.0.7.
pmdarima 1.8.5 requires scipy, which is not installed.
onnxruntime 1.14.1 has requirement numpy>=1.21.6, but you have numpy 1.21.3.
mlflow-skinny 1.30.1 has requirement packaging<22, but you have packaging 24.0.
mlflow-skinny 1.30.1 has requirement pytz<2023, but you have pytz 2025.2.
mlflow-skinny 1.30.1 has requirement importlib-metadata!=4.7.0,<6,>=3.7.0, but you have importlib-metadata 6.7.0.
ml-wrappers 0.5.6 requires scipy, which is not installed.
lightgbm 3.2.1 requires scipy, which is not installed.
interpret-community 0.31.0 requires scipy, which is not installed.
gensim 3.8.3 requires scipy, which is not installed.
botocore 1.23.19 has requirement jmespath<1.0.0,>=0.7.1, but you have jmespath 1.0.1.
boto3 1.20.19 has requirement jmespath<1.0.0,>=0.7.1, but you have jmespath 1.0.1.
azureml-training-tabular 1.55.0.post1 requires scipy, which is not installed.
azureml-train-automl-runtime 1.55.0.post1 requires scipy, which is not installed.
azureml-train-automl-runtime 1.55.0.post1 has requirement pyarrow==14.0.2, but you have pyarrow 12.0.1.
azureml-train-automl-runtime 1.55.0.post1 has requirement scikit-learn==1.1.3, but you have scikit-learn 1.0.2.
azureml-automl-runtime 1.55.0.post1 requires scipy, which is not installed.
azureml-automl-runtime 1.55.0.post1 has requirement scikit-learn==1.1.3, but you have scikit-learn 1.0.2.
azureml-automl-dnn-vision 1.55.0.post2 requires scikit-image, which is not installed.
arch 5.3.1 requires scipy, which is not installed.

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Important

• Check the changes in this PR to ensure they won't cause issues with your project.
• Max score is 1000. Note that the real score may have changed since the PR was raised.
• This PR was automatically created by Snyk using the credentials of a real user.
• Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

---

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[gemini-code-assist]

Summary of Changes

Hello @q1blue, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request, automatically generated by Snyk, addresses four security vulnerabilities within the project's Python dependencies. It updates specific package versions in responsibleai_vision/requirements-automl.txt to mitigate these risks, ensuring the project's security posture is improved.

Highlights

• Dependency Updates: The pull request introduces updates for pyasn1, torch, and wheel in the responsibleai_vision/requirements-automl.txt file.
• Vulnerability Fixes: These dependency updates are specifically aimed at resolving 4 identified security vulnerabilities, as indicated by Snyk.

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[gemini-code-assist]

Code Review

This pull request from Snyk proposes upgrading pyasn1, torch, and wheel to address security vulnerabilities. While security is crucial, these changes, especially the major version upgrade of torch to 2.x, pose a critical risk of breaking the project. The PR description itself includes a long list of existing dependency conflicts, indicating a fragile environment. Merging this PR will likely exacerbate these issues and lead to a non-functional state. The upgrade of torch from 1.13.1 to >=2.10.0 is a major change that often includes breaking APIs, and it conflicts with the project's apparent strategy of avoiding major version bumps for key libraries like numpy and pydantic. Due to the high probability of introducing breaking changes and dependency conflicts, I recommend not merging this PR as is. A more robust approach is needed: first, address the existing dependency conflicts reported in the PR description; second, carefully evaluate the torch upgrade, addressing any necessary code changes; and third, consider using a dependency management tool like pip-tools to create a consistent, locked set of dependencies. This will ensure that security vulnerabilities are fixed without compromising the stability of the project.

[gemini-code-assist]

This change introduces a major version upgrade for torch (from 1.x to >=2.10.0). This is a significant risk and is likely to introduce breaking API changes, which could break existing functionality that depends on torch (e.g., via torchmetrics). Other dependencies in this project, like pydantic and numpy, are carefully pinned to avoid major version upgrades, and the same caution should be applied here. Additionally, pinning transitive dependencies in this file can lead to a fragile dependency setup. The extensive list of warnings in the pull request description indicates that the dependency tree is already inconsistent. Merging these changes without resolving the underlying conflicts will likely break the environment. It is strongly recommended to reject this automated change and instead perform a comprehensive update of dependencies, resolving all conflicts, and thoroughly testing the application.