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Transformers CVE-2025-5197

MEDIUM
Inefficient Regular Expression Complexity (ReDoS) (CWE-1333)
2025-08-06 security@huntr.dev
5.3
CVSS 3.0 · NVD
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Severity by source

NVD PRIMARY
5.3 MEDIUM
AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
SUSE
MEDIUM
qualitative
Red Hat
5.3 MEDIUM
qualitative

Primary rating from NVD.

CVSS VectorNVD

CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
Low

Lifecycle Timeline

4
Analysis Generated
Mar 28, 2026 - 19:05 vuln.today
Patch released
Mar 28, 2026 - 19:05 nvd
Patch available
PoC Detected
Oct 21, 2025 - 16:46 vuln.today
Public exploit code
CVE Published
Aug 06, 2025 - 12:15 nvd
MEDIUM 5.3

Blast Radius

ecosystem impact
† from your stack dependencies † transitive graph · vuln.today resolves 4-path depth
  • 14 pypi packages depend on transformers (14 direct, 0 indirect)

Ecosystem-wide dependent count for version 4.53.0.

DescriptionCVE.org

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.

AnalysisAI

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. Rated medium severity (CVSS 5.3), this vulnerability is remotely exploitable, no authentication required, low attack complexity. Public exploit code available.

Technical ContextAI

This vulnerability is classified under CWE-1333. 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 products include: Huggingface Transformers. Version information: up to 4.51.3.

RemediationAI

A vendor patch is available. Apply the latest security update as soon as possible. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.

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CVE-2023-6730 HIGH POC
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CVE-2023-7018 HIGH POC
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CVE-2025-3262 HIGH POC
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CVE-2025-3933 MEDIUM POC
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CVE-2024-11394 HIGH
8.8 Nov 22

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CVE-2024-11393 HIGH
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Hugging Face Transformers MaskFormer Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. Rated

Vendor StatusVendor

SUSE

Severity: Medium

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CVE-2025-5197 vulnerability details – vuln.today

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