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[Snyk] Fix for 2 vulnerabilities#709

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snyk-fix-14fc6378267cb88e52953236449eb8c2
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[Snyk] Fix for 2 vulnerabilities#709
alejandrosuarez wants to merge 1 commit intomainfrom
snyk-fix-14fc6378267cb88e52953236449eb8c2

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@alejandrosuarez alejandrosuarez commented Jan 31, 2026

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Snyk has created this PR to fix 2 vulnerabilities in the pip dependencies of this project.

Snyk changed the following file(s):

  • examples/custom_diffusion/requirements.txt
⚠️ Warning 
transformers 4.30.2 requires safetensors, which is not installed.
torchvision 0.14.1 requires torch, which is not installed.
tensorboard 2.11.2 requires protobuf, which is not installed.
accelerate 0.20.3 requires torch, which is not installed.

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  • 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 bot commented Jan 31, 2026

Summary of Changes

Hello @alejandrosuarez, 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, aims to enhance the security posture of the project by resolving two critical vulnerabilities found in its pip dependencies. It achieves this by introducing explicit version requirements for protobuf and torch within the examples/custom_diffusion/requirements.txt file, ensuring that secure versions of these packages are used.

Highlights

  • Vulnerability Fixes: This pull request, automatically generated by Snyk, addresses two identified security vulnerabilities within the project's pip dependencies.
  • Dependency Upgrades: The examples/custom_diffusion/requirements.txt file has been updated to include specific version pins for protobuf (to >=6.33.5) and torch (to >=2.10.0).
  • Indirect Dependencies: Snyk indicates that protobuf and torch are not direct requirements but are pinned to these versions to mitigate the discovered vulnerabilities.
  • Potential Warnings: The PR description includes a warning regarding other packages (transformers, torchvision, tensorboard, accelerate) that may have unmet or incompatible dependencies with the current environment, specifically mentioning safetensors, torch, and protobuf.
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socket-security bot commented Jan 31, 2026

Review the following changes in direct dependencies. Learn more about Socket for GitHub.

Diff Package Supply Chain
Security		 Vulnerability Quality Maintenance License
Addedprotobuf@​6.33.5100100100100100

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gemini-code-assist[bot]
gemini-code-assist bot reviewed Jan 31, 2026
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Code Review

This pull request, automatically generated by Snyk, attempts to fix security vulnerabilities by upgrading protobuf and torch. However, the proposed versions are problematic. The specified protobuf version is invalid and conflicts with other dependencies, which is a critical issue. The torch version is also likely invalid and represents a major version jump that risks breaking the example code. I have left a detailed comment explaining the issues and recommend that this PR be rejected in favor of a manual and carefully tested dependency update.

examples/custom_diffusion/requirements.txt
Comment on lines +7 to +8
protobuf>=6.33.5 # not directly required, pinned by Snyk to avoid a vulnerability
torch>=2.10.0 # not directly required, pinned by Snyk to avoid a vulnerability
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critical

This automated dependency update introduces several critical issues and will likely break the project.

  1. protobuf>=6.33.5: This is invalid.

    • The version 6.33.5 does not exist for the protobuf package on PyPI.
    • Even if it were a typo for a 4.x+ version, it would conflict with other dependencies. For example, tensorboard often requires protobuf<4. This would cause the installation to fail.

  2. torch>=2.10.0: This is a high-risk upgrade.

    • The version 2.10.0 does not appear to be a valid torch release.
    • The jump from torch 1.x to 2.x is a major change that can introduce breaking changes. The example script was likely not written or tested for torch 2.x. Dependencies like torchvision would also need to be updated to maintain compatibility.

Given these issues, I strongly recommend rejecting this automated PR. The vulnerabilities should be addressed with a manual update where compatible and valid package versions are chosen and thoroughly tested.

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