# CVE-2025-5197: transformers DoS — Fixed in 4.53.0

🐍

🐍 PyPI

Not in CISA KEV

MEDIUM severity

# CVE-2025-5197 — transformers

MEDIUM [Fix: huggingface/transformers@944b560](https://github.com/huggingface/transformers/commit/944b56000be5e9b61af8301aa340838770ad8a0b)

CVE-2025-5197 is a medium-severity (CVSS 5.3) CWE-1333 vulnerability in transformers. A fix is available for transformers — see the affected versions and patch details below.

Regular Expression Denial of Service (ReDoS) in huggingface/transformers

Also known as[GHSA-9356-575x-2w9m](/vulnerability/GHSA-9356-575x-2w9m)PYSEC-2026-1983

Published

Aug 6, 2025

Updated

Oct 28, 2026

Affected

1 pkg

Patched

1 / 1

Exploits

None indexed

Exploitation data as of Nov 5, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

## Exploitation Status

### Proof-of-concept exploit code exists

-   CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
-   CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.

Exploitation and automatability from CISA’s SSVC triage for CVE-2025-5197.

## EPSS Exploitation Probability

[via FIRST.org ↗](https://www.first.org/epss/)

0.4%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs36th percentile — riskier than 36% of all scored CVEsHighest risk

0.00%0.31%0.61%0.92%0.0%0.4%May 26Sep 26Nov 26

Probability of exploitation in the next 30 days, from [FIRST.org EPSS](https://www.first.org/epss/).

## How urgent is this, really

## Where this sits among everything scored

## Real-World Exposure

1 pkg affected

🐍`transformers`

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

## Description

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.

## Affected Packages

1 total 1 fixed

Ecosystem

Package

Vulnerable range

Fix

🐍PyPI

`transformers` 

all versions

4.53.0`pip install --upgrade 'transformers==4.53.0'`

## Affected Products

1 product · 1 configurations

Application

`transformers`huggingface

< 4.53.0

range

## Detection & mitigation playbook

Open-source dependency

1.  ### Detect
    
    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for transformers, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
    
2.  ### Fix
    
    Update transformers to 4.53.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2025-5197 is resolved across your whole dependency graph.
    
3.  ### Workarounds
    
    Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.
    

## Fixing This On Your OS

If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.

Red HatModerate

Workaround published by Red Hat

> Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.

Source: [Red Hat security advisory for CVE-2025-5197](https://access.redhat.com/security/cve/cve-2025-5197) (CC BY 4.0)

## Frequently Asked Questions

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 servic

O3 Security · Impact-Aware SCA

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