TransformersApplication · Huggingface

CVE-2025-14928

HIGH · 7.8 CVSS v3.0 Published 2025-12-23
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
81/100
Remediation priority · High
No privileges

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
Hugging Face Transformers HuBERT convert_config Code Injection Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must convert a malicious checkpoint. The specific flaw exists within the convert_config function. The issue results from the lack of proper validation of a user-supplied string before using it to execute Python code. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-28253.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · moderate confidence

A code injection vulnerability exists in Hugging Face Transformers' HuBERT convert_config function where user-supplied strings from malicious model checkpoints are executed as Python code without validation, allowing arbitrary code execution in the context of the current user.

MitigationImplement strict input validation on all checkpoint configuration strings before execution, avoid using eval()/exec() with untrusted data, and sandbox the checkpoint conversion process. Users should not convert checkpoints from untrusted sources.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.

NVD · CPE data
TransformersApplication
Affected:= 4.57.0

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Local
Complexity
Low
Privileges
None
User interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Check installed Transformers version
    Run: pip show transformers | grep Version or import transformers; print(transformers.__version__)
    Affected if Version is exactly 4.57.0
  2. Identify HuBERT checkpoint conversion usage
    Search codebase for convert_config calls related to HubertModel, or inspect model loading scripts for HuBERT-specific conversion logic
    Affected if Code uses HuBERT convert_config or loads HuBERT checkpoints from untrusted sources
  3. Inspect model checkpoint config files
    Examine config.json or config.yaml files in the model checkpoint directory for unusual string values that could be malicious code
    Affected if Checkpoint config contains suspicious Python code strings in fields that get eval'd/exec'd
  4. Check for eval or exec usage in convert_config
    Review the transformers library code: look for eval()/exec() calls in hubert feature extraction or convert_config modules
    Affected if The convert_config function uses eval/exec on unvalidated checkpoint strings

You are affected if you are running Transformers 4.57.0 and using it to convert or load HuBERT checkpoints, especially from untrusted or unverified sources, without input validation on checkpoint configuration strings.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

dbcve · scoped
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Implement strict input validation on all checkpoint configuration strings before execution, avoid using eval()/exec() with untrusted data, and sandbox the checkpoint conversion process. Users should not convert checkpoints from untrusted sources.

Recommended fix Moderate confidence

Latest stable Transformers release (version > 4.57.0)

  1. 1. Identify all systems running Hugging Face Transformers version 4.57.0 in your environment
  2. 2. Upgrade Transformers to the latest stable release using: pip install --upgrade transformers
  3. 3. Verify the upgrade completed successfully by running: python -c 'import transformers; print(transformers.__version__)'
  4. 4. If using a specific environment, ensure the upgrade is applied to that environment (e.g., virtualenv, conda, Docker container)
  5. 5. Test any code that uses the convert_config function to ensure normal operation after upgrade
  6. 6. Review any custom checkpoint conversion code to ensure it does not pass unsanitized input to the convert_config function as a defensive measure
Caveat Likely minimal; minor version upgrades in Hugging Face Transformers typically maintain backward compatibility for core functionality

Generated from the published advisory — verify against the referenced sources before acting.

Fix this in Transformers Scoped from the published advisory
  • Consultation4.0 h
  • Implementation8.0 h
  • Testing6.0 h
  • Review / QA4.0 h
22.0 hours of engineering $3,860
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2025-14928 in production — separate from our analysis above.

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