IndicoDataSolutions / finetune

Scikit-learn style model finetuning for NLP
https://finetune.indico.io
Mozilla Public License 2.0
703 stars 80 forks source link

[Snyk] Security upgrade tensorflow/tensorflow from 2.15.0-gpu to 2.18.0rc1-gpu #818

Open sihrc opened 1 month ago

sihrc commented 1 month ago

snyk-top-banner

Snyk has created this PR to fix 5 vulnerabilities in the dockerfile dependencies of this project.

Keeping your Docker base image up-to-date means you’ll benefit from security fixes in the latest version of your chosen image.

Snyk changed the following file(s):

We recommend upgrading to tensorflow/tensorflow:2.18.0rc1-gpu, as this image has only 83 known vulnerabilities. To do this, merge this pull request, then verify your application still works as expected.

Vulnerabilities that will be fixed with an upgrade:

Issue Score
high severity CVE-2023-44487
SNYK-UBUNTU2204-NGHTTP2-5954819
  829  
medium severity Improper Validation of Integrity Check Value
SNYK-UBUNTU2204-LIBSSH-6130572
  621  
medium severity CVE-2024-6923
SNYK-UBUNTU2204-PYTHON310-7577352
  514  
medium severity CVE-2024-8088
SNYK-UBUNTU2204-PYTHON310-7830061
  514  
medium severity Inefficient Regular Expression Complexity
SNYK-UBUNTU2204-PYTHON310-7922967
  514  

[!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.

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:

🦉 Inefficient Regular Expression Complexity