Vulnerability in Huggingface Huggingface/transformers
CVE-2025-5197
A Regular Expression Denial of Service (ReDoS) vulnerability exists in the Hugging Face Transformers library, specifically in the `convert_tf_weight_name_to_pt_weight_name()` function. This function, responsible for converting TensorFlow weight names to PyTorch format, uses a regex pattern `/[^/]*___([^/]*)/` that can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. The vulnerability affects versions up to 4.51.3 and is fixed in version 4.53.0. This issue can lead to service disruption, resource exhaustion, and potential API service vulnerabilities, impacting model conversion processes between TensorFlow and PyTorch formats.
Vulnerability class: ReDoS (Regular Expression Denial of Service)
EPSS: 0.004 (32.7th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 5.3 (Medium). Vector: CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L.
Affected products
- Huggingface Huggingface/transformers — versions unspecified
- Huggingface Transformers
Weakness classification (CWE)
References
- security@huntr.dev (Exploit, Patch, Third Party Advisory, Issue Tracking)
- security@huntr.dev (Patch)
Frequently asked questions
- What is CVE-2025-5197?
- CVE-2025-5197 is a medium-severity vulnerability in Huggingface Huggingface/transformers, classified under Inefficient Regular Expression Complexity. CVSS score: 5.3/10. Published 2025-08-06.
- How severe is CVE-2025-5197?
- Medium severity. CVSS v3 base score is 5.3 out of 10.