Transformers-4.49.0-py3-none-any.whl: 1 Vulnerabilities (highest Severity Is: 5.3) Unreachable
Introduction
The transformers library is a popular and widely-used library for natural language processing (NLP) tasks. It provides a range of pre-trained models and tools for tasks such as language translation, text classification, and question answering. However, like all software, it is not immune to vulnerabilities. In this article, we will discuss a vulnerability in the transformers library, specifically in the version 4.49.0, and how to remediate it.
Vulnerability Details
The vulnerability in question is a Regular Expression Denial of Service (ReDoS) vulnerability, which was identified in the huggingface/transformers library, specifically in the file "tokenization_gpt_neox_japanese.py" of the GPT-NeoX-Japanese model. The vulnerability occurs in the SubWordJapaneseTokenizer class, where regular expressions process specially crafted inputs. The issue stems from a regex exhibiting exponential complexity under certain conditions, leading to excessive backtracking. This can result in high CPU usage and potential application downtime, effectively creating a Denial of Service (DoS) scenario.
Vulnerable Library - transformers-4.49.0-py3-none-any.whl
The vulnerable library is transformers-4.49.0-py3-none-any.whl, which is a Python wheel file that contains the transformers library. The library home page is located at https://files.pythonhosted.org/packages/20/37/1f29af63e9c30156a3ed6ebc2754077016577c094f31de7b2631e5d379eb/transformers-4.49.0-py3-none-any.whl.
Dependency Hierarchy
The dependency hierarchy for the vulnerable library is as follows:
- :x: transformers-4.49.0-py3-none-any.whl (Vulnerable Library)
Reachability Analysis
The vulnerable code is unreachable, which means that the vulnerability is not currently being exploited.
Vulnerability Details
The vulnerability details are as follows:
- Publish Date: 2025-04-29
- URL: CVE-2025-1194
Threat Assessment
The threat assessment for the vulnerability is as follows:
- Exploit Maturity: Not Defined
- EPSS: 0.1%
CVSS 4 Score Details
The CVSS 4 score details for the vulnerability are as follows:
- Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: N/A
- Scope: N/A
- Impact Metrics:
- Confidentiality Impact: N/A
- Integrity Impact: N/A
- Availability Impact: N/A
Suggested Fix
The suggested fix for the vulnerability is to upgrade the transformers library to version 4.50.0, which is the latest version that fixes the vulnerability.
Remediation
To remediate the vulnerability, you can follow these steps:
- Upgrade the transformers library to version 4.50.0 using pip:
pip install transformers==4.500 - Verify that the vulnerability has been fixed by running the following command:
python -c "import transformers; print(transformers.__version__)"
Conclusion
In conclusion, the transformers library version 4.49.0 contains a ReDoS vulnerability that can be exploited to create a Denial of Service (DoS) scenario. The vulnerability is currently unreachable, but it is essential to upgrade the library to version 4.50.0 to fix the issue. By following the remediation steps outlined above, you can ensure that your application is secure and free from vulnerabilities.
In order to enable automatic remediation for this issue, please create workflow rules
Introduction
In our previous article, we discussed a vulnerability in the transformers library, specifically in the version 4.49.0. In this article, we will answer some frequently asked questions (FAQs) related to the vulnerability.
Q: What is the transformers library?
A: The transformers library is a popular and widely-used library for natural language processing (NLP) tasks. It provides a range of pre-trained models and tools for tasks such as language translation, text classification, and question answering.
Q: What is the vulnerability in the transformers library?
A: The vulnerability in the transformers library is a Regular Expression Denial of Service (ReDoS) vulnerability, which was identified in the huggingface/transformers library, specifically in the file "tokenization_gpt_neox_japanese.py" of the GPT-NeoX-Japanese model.
Q: What is a ReDoS vulnerability?
A: A ReDoS vulnerability is a type of vulnerability that occurs when a regular expression is used to process specially crafted inputs, leading to excessive backtracking and potentially causing a Denial of Service (DoS) scenario.
Q: How does the ReDoS vulnerability affect the transformers library?
A: The ReDoS vulnerability in the transformers library can cause high CPU usage and potential application downtime, effectively creating a Denial of Service (DoS) scenario.
Q: Is the vulnerability currently being exploited?
A: No, the vulnerable code is unreachable, which means that the vulnerability is not currently being exploited.
Q: How can I remediate the vulnerability?
A: To remediate the vulnerability, you can upgrade the transformers library to version 4.50.0, which is the latest version that fixes the vulnerability.
Q: How do I upgrade the transformers library to version 4.50.0?
A: You can upgrade the transformers library to version 4.50.0 using pip: pip install transformers==4.500
Q: How do I verify that the vulnerability has been fixed?
A: You can verify that the vulnerability has been fixed by running the following command: python -c "import transformers; print(transformers.__version__)"
Q: Can I enable automatic remediation for this issue?
A: Yes, you can enable automatic remediation for this issue by creating workflow rules
Q: What is the CVSS 4 score for the vulnerability?
A: The CVSS 4 score for the vulnerability is 5.3, which indicates a high severity vulnerability.
Q: What is the EPSS for the vulnerability?
A: The EPSS for the vulnerability is 0.1%, which indicates a low likelihood of exploitation.
Q: What is the recommended fix for the vulnerability?
A: The recommended fix for the vulnerability is to upgrade the transformers library to version 4.50.0.
Q: Can I use the transformers library in production with the current vulnerability?
A: No, it is not recommended to use the transformers library in production with the current vulnerability, as it can cause high CPU usage and potential application downtime.
Q: How can I stay up-to-date with the latest security patches for the transformers library?
A: You can stay up-to-date with the latest security patches for the transformers library by following the official GitHub repository and checking for updates regularly.
Q: Can I report a vulnerability in the transformers library?
A: Yes, you can report a vulnerability in the transformers library by submitting a pull request to the official GitHub repository.
Q: How can I get help with remediating the vulnerability?
A: You can get help with remediating the vulnerability by contacting the official support team or seeking help from a security expert.