AdamOswald / Huggingface-Space

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[Snyk] Security upgrade validators from 0.20.0 to 0.21.0 #83

Open AdamOswald opened 11 months ago

AdamOswald commented 11 months ago

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-cublas-cu11, which is not installed. torch 1.13.1 requires nvidia-cuda-runtime-cu11, which is not installed. tensorboard 2.11.2 has requirement protobuf<4,>=3.9.2, but you have protobuf 4.24.4. tensorboard 2.11.2 has requirement setuptools>=41.0.0, but you have setuptools 39.0.1. streamlit 1.23.1 requires validators, which is not installed. 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 multiprocess<=0.70.12.2, but you have multiprocess 0.70.15. paddlenlp 2.6.1 has requirement protobuf==3.20.2, but you have protobuf 4.24.4. 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. 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 1.31.67 has requirement urllib3<1.27,>=1.25.4; python_version < "3.10", but you have urllib3 2.0.7. ```
#### Vulnerabilities that will be fixed ##### By pinning: Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- ![medium severity](https://res.cloudinary.com/snyk/image/upload/w_20,h_20/v1561977819/icon/m.png "medium severity") | **623/1000**
**Why?** Proof of Concept exploit, Recently disclosed, Has a fix available, CVSS 4.6 | Regular Expression Denial of Service (ReDoS)
[SNYK-PYTHON-VALIDATORS-6008990](https://snyk.io/vuln/SNYK-PYTHON-VALIDATORS-6008990) | `validators:`
`0.20.0 -> 0.21.0`
| No | Proof of Concept (*) 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: 🧐 [View latest project report](https://app.snyk.io/org/adamoswald/project/b75960b5-8cdf-4db3-b4dc-2ee6bd89b8a7?utm_source=github&utm_medium=referral&page=fix-pr) 🛠 [Adjust project settings](https://app.snyk.io/org/adamoswald/project/b75960b5-8cdf-4db3-b4dc-2ee6bd89b8a7?utm_source=github&utm_medium=referral&page=fix-pr/settings) 📚 [Read more about Snyk's upgrade and patch logic](https://support.snyk.io/hc/en-us/articles/360003891078-Snyk-patches-to-fix-vulnerabilities) [//]: # (snyk:metadata:{"prId":"ac78ecba-2aad-4351-a419-f20836699b1e","prPublicId":"ac78ecba-2aad-4351-a419-f20836699b1e","dependencies":[{"name":"validators","from":"0.20.0","to":"0.21.0"}],"packageManager":"pip","projectPublicId":"b75960b5-8cdf-4db3-b4dc-2ee6bd89b8a7","projectUrl":"https://app.snyk.io/org/adamoswald/project/b75960b5-8cdf-4db3-b4dc-2ee6bd89b8a7?utm_source=github&utm_medium=referral&page=fix-pr","type":"auto","patch":[],"vulns":["SNYK-PYTHON-VALIDATORS-6008990"],"upgrade":[],"isBreakingChange":false,"env":"prod","prType":"fix","templateVariants":["updated-fix-title","pr-warning-shown","priorityScore"],"priorityScoreList":[623],"remediationStrategy":"vuln"}) --- **Learn how to fix vulnerabilities with free interactive lessons:** 🦉 [Regular Expression Denial of Service (ReDoS)](https://learn.snyk.io/lesson/redos/?loc=fix-pr)
secure-code-warrior-for-github[bot] commented 11 months ago

Micro-Learning Topic: Regular expression denial of service (Detected by phrase)

Matched on "Regular Expression Denial of Service"

What is this? (2min video)

Denial of Service (DoS) attacks caused by Regular Expression which causes the system to hang or cause them to work very slowly when attacker sends a well-crafted input(exponentially related to input size).Denial of service attacks significantly degrade the service quality experienced by legitimate users. These attacks introduce large response delays, excessive losses, and service interruptions, resulting in direct impact on availability.

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Micro-Learning Topic: Denial of service (Detected by phrase)

Matched on "Denial of Service"

The Denial of Service (DoS) attack is focused on making a resource (site, application, server) unavailable for the purpose it was designed. There are many ways to make a service unavailable for legitimate users by manipulating network packets, programming, logical, or resources handling vulnerabilities, among others. Source: https://www.owasp.org/index.php/Denial_of_Service

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