Hugging Face CVE-2025-5197
MEDIUMVulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A06:2021 - Vulnerable and Outdated Components
ASVS 5.0
V2 - Validation and Business Logic Regex complexity limits
MITRE ATT&CK
1 technique across 1 tactic: Impact The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Impact | CVSS score of 5.3 (MEDIUM). Attack characteristics: network attack vector, low complexity, no privileges required, no user interaction not required. Public proof-of-concept exploit code is available. EPSS exploitation probability: 0.03%. |
| Exploit ScenarioDerived | This vulnerability can be exploited remotely over the network. Successful exploitation could compromise the medium-severity affected system. |
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Alert meAnalysisAIv1 – Mar 28, 2026
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.
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.
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in pypi
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
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.
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Severity by source
AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Primary rating from NVD.
CVSS VectorNVD
Lifecycle Timeline
3DescriptionCVE.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.
Executive ViewAI
CVE-2025-5197 presents moderate security risk rated CVSS 5.3. Exploitation could compromise the security of affected deployments. Proof-of-concept code is publicly available. A patch is available and should be applied during regular vulnerability management.
Apply vendor patch. If patching is delayed: restrict network access and enable monitoring.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Denial of Service attacks render applications or systems unavailable by overwhelming resources or triggering failure conditions.
Affected Products (CPE)CVE.org
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GitHub PoC
Exploit-DB