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TransformersApplication · Huggingface

CVE-2025-14926

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 SEW 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-28251.

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 · high confidence

A code injection vulnerability in Hugging Face Transformers' convert_config function allows remote attackers to execute arbitrary Python code by tricking users into converting a malicious checkpoint. The flaw stems from insufficient validation of user-supplied strings before they're passed to Python's exec() or similar evaluation functions.

MitigationUsers should avoid converting checkpoints from untrusted sources until a patch is applied. The fix requires adding strict input validation to ensure user-supplied strings in convert_config cannot be interpreted as executable Python code.

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' or 'import transformers; print(transformers.__version__)' to see the installed version
    Affected if Version equals 4.57.0 exactly (the only affected version listed)
  2. Identify use of convert_config function
    Search codebases for imports or calls to 'convert_config' from the transformers library, or inspect any scripts that process model checkpoints
    Affected if The convert_config function is imported and used in any processing pipeline
  3. Inspect checkpoint conversion workflows
    Review any code that loads, parses, or converts model checkpoints, particularly where config files are processed
    Affected if User-supplied or untrusted checkpoint files are being converted using convert_config
  4. Check for exec() or eval() usage in config parsing
    Search the transformers library code for exec() or eval() calls within conversion-related modules (look in transformers/src/transformers/)
    Affected if The convert_config function contains unsafe evaluation of user strings before the fix
  5. Review checkpoint sources
    Identify where model checkpoints originate - whether from trusted Hugging Face Hub, local trusted sources, or untrusted/third-party sources
    Affected if Checkpoints from untrusted or unknown sources are being converted

You are affected if you have Transformers version 4.57.0 installed AND use the convert_config function to process checkpoints, especially from untrusted sources.

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.

From vendor data
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Users should avoid converting checkpoints from untrusted sources until a patch is applied. The fix requires adding strict input validation to ensure user-supplied strings in convert_config cannot be interpreted as executable Python code.

Fix this in Transformers Scoped from the published advisory
  • Consultation3.0 h
  • Implementation6.0 h
  • Testing5.0 h
  • Review / QA3.0 h
17.0 hours of engineering $2,970
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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-2025-14926 in production — separate from our analysis above.

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What this is

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What belongs here
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  • Version or environment caveats, and links to real fixes
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