CVE-2025-5197 Regular Expression Denial of Service (ReDoS) in huggingface/transformers

Medium 5.3 Published Updated

Attackers can cause service disruption and resource exhaustion in Hugging Face Transformers via crafted input triggering catastrophic regex backtracking.

Exploited in the wild
Not known
Login needed
Not needed
Attackable
Over the internet
Victim action needed
Not needed
Fix
Available

What is CVE-2025-5197?

CVE-2025-5197 is a medium-severity denial of service vulnerability in huggingface/transformers, published on 6 Aug 2025. An attacker can exploit it over the internet without logging in, with no action from the victim.

Official 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.

Weakness: CWE-1333

Which versions are affected by CVE-2025-5197?

3 open source packages ship an affected version, including transformers. It affects 1 product.

PackageAffectedFixed in
transformers PyPIAll versions4.53.0
transformers PyPIAll versions4.53.0
transformers PyPIAll versions4.53.0

Products include Huggingface Transformers.

How do I fix CVE-2025-5197?

Upgrade transformers to 4.53.0 or later.

Upgrade, then put limits on request size, rate and nesting depth so one client cannot exhaust the service. More about Denial of service.

Is CVE-2025-5197 being exploited?

It is not confirmed as exploited in the wild, but public exploit code for CVE-2025-5197 exists.

Sources

Also known as GHSA-9356-575x-2w9m, PYSEC-2026-1983.

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