Inefficient Regular Expression Complexity Affecting text-generation-inference package, versions <3.3.6-r0
Threat Intelligence
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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Start learning- Snyk IDSNYK-CHAINGUARDLATEST-TEXTGENERATIONINFERENCE-13600364
- published17 Oct 2025
- disclosed6 Aug 2025
Introduced: 6 Aug 2025
CVE-2025-5197 (opens in a new tab)How to fix?
Upgrade Chainguard text-generation-inference to version 3.3.6-r0 or higher.
NVD Description
Note: Versions mentioned in the description apply only to the upstream text-generation-inference package and not the text-generation-inference package as distributed by Chainguard.
See How to fix? for Chainguard relevant fixed versions and status.
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.