Closed AdamOswald closed 9 months ago
sonarcloud[bot]
commented
10 months ago Kudos, SonarCloud Quality Gate passed! 
0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells
No Coverage information
No Duplication information
sonarcloud[bot]
commented
9 months ago Kudos, SonarCloud Quality Gate passed!
0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells
No Coverage information
No Duplication information
This PR was automatically created by Snyk using the credentials of a real user.
Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.
#### Changes included in this PR - Changes to the following files to upgrade the vulnerable dependencies to a fixed version: - requirements.txt⚠️ Warning
``` transformers 4.30.2 has requirement tokenizers!=0.11.3,<0.14,>=0.11.1, but you have tokenizers 0.14.1. torch 1.13.1 requires nvidia-cudnn-cu11, which is not installed. torch 1.13.1 requires nvidia-cuda-nvrtc-cu11, which is not installed. torch 1.13.1 requires nvidia-cuda-runtime-cu11, which is not installed. torch 1.13.1 requires nvidia-cublas-cu11, which is not installed. tensorboard 2.11.2 requires werkzeug, which is not installed. tensorboard 2.11.2 has requirement setuptools>=41.0.0, but you have setuptools 39.0.1. tensorboard 2.11.2 has requirement protobuf<4,>=3.9.2, but you have protobuf 4.24.4. scikit-learn 1.0.2 requires scipy, which is not installed. python-igraph 0.11.2 has requirement igraph==0.11.2, but you have igraph 0.10.8. powerlaw 1.5 requires scipy, which is not installed. pipenv 2023.10.3 has requirement setuptools>=67, but you have setuptools 39.0.1. paddlenlp 2.6.1 requires seqeval, which is not installed. paddlenlp 2.6.1 has requirement dill<0.3.5, but you have dill 0.3.7. paddlenlp 2.6.1 has requirement protobuf==3.20.2, but you have protobuf 4.24.4. paddlenlp 2.6.1 has requirement multiprocess<=0.70.12.2, but you have multiprocess 0.70.15. paddle2onnx 0.9.5 has requirement onnx<=1.9.0, but you have onnx 1.14.1. onnxruntime 1.14.1 has requirement numpy>=1.21.6, but you have numpy 1.21.3. onnxruntime-gpu 1.14.1 has requirement numpy>=1.21.6, but you have numpy 1.21.3. lpips 0.1.4 requires scipy, which is not installed. Flask 2.2.5 requires Werkzeug, which is not installed. filterpy 1.4.5 requires scipy, which is not installed. facexlib 0.3.0 requires scipy, which is not installed. datasets 2.13.2 has requirement dill<0.3.7,>=0.3.0, but you have dill 0.3.7. botocore 1.31.72 has requirement urllib3<1.27,>=1.25.4; python_version < "3.10", but you have urllib3 2.0.7. ```**Why?** Recently disclosed, Has a fix available, CVSS 6.5 | Inefficient Algorithmic Complexity
[SNYK-PYTHON-WERKZEUG-6035177](https://snyk.io/vuln/SNYK-PYTHON-WERKZEUG-6035177) | `werkzeug:`
`2.2.3 -> 3.0.1`
| No | No Known Exploit (*) Note that the real score may have changed since the PR was raised. 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. Check the changes in this PR to ensure they won't cause issues with your project. ------------ **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: