[Snyk] Security upgrade transformers from 4.22.2 to 5.0.0rc1#81
[Snyk] Security upgrade transformers from 4.22.2 to 5.0.0rc1#81
Conversation
…abilities The following vulnerabilities are fixed by pinning transitive dependencies: - https://snyk.io/vuln/SNYK-PYTHON-TRANSFORMERS-14564337
There was a problem hiding this comment.
Pull request overview
This PR upgrades the transformers library from version 4.22.2 to 5.0.0rc1 to address a security vulnerability (SNYK-PYTHON-TRANSFORMERS-14564337) related to deserialization of untrusted data. While the intent is to fix a security issue, the proposed upgrade introduces significant risks by jumping to a pre-release version and a major version change.
Key Changes:
- Security upgrade of transformers package to address vulnerability SNYK-PYTHON-TRANSFORMERS-14564337
- Major version bump from 4.x to 5.x (release candidate)
💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.
| streamlit==1.13.0 | ||
| streamlit-image-comparison==0.0.2 | ||
| transformers==4.22.2 | ||
| transformers==5.0.0rc1 |
There was a problem hiding this comment.
Using a release candidate version (5.0.0rc1) in production dependencies is not recommended. Release candidates are pre-release versions intended for testing and may contain bugs or unstable features. Consider upgrading to a stable version instead, such as 4.46.0 or the latest stable 4.x release that addresses the security vulnerability, or wait for the stable 5.0.0 release.
| transformers==5.0.0rc1 | |
| transformers==4.46.0 |
Snyk has created this PR to fix 1 vulnerabilities in the pip dependencies of this project.
Snyk changed the following file(s):
src/stable-diffusion-streamlit/requirements.txtImportant
Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.
For more information:
🧐 View latest project report
📜 Customise PR templates
🛠 Adjust project settings
📚 Read about Snyk's upgrade logic
Learn how to fix vulnerabilities with free interactive lessons:
🦉 Deserialization of Untrusted Data