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VulnerabilityPublished

CVE-2025-14927: Hugging Face Transformers · Code Injection

Affects Hugging Face TransformersSource CVE Database V5

0

Not known to be exploited · CVSS 7.8 High.

Data as of 26 Oct 2026, 10:12 UTC

CVSS 3.0 base score
7.8High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.3% chance of exploitation in 30 days – higher than 27% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 23 Dec 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

What to do

Affected software

ProductAffectedFixed in
PyPItransformerspkg:pypi/transformersOther threatsAffected
  • =4.57.0
Fixed in–

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AI-suggested

To mitigate CVE-2025-14927, European organizations should: 1) Immediately avoid converting or loading checkpoint files from untrusted or unauthenticated sources to prevent malicious input. 2) Monitor for updates from Hugging Face and apply security patches promptly once released. 3) Implement strict input validation and sanitization around any user-supplied configuration or checkpoint data before processing. 4) Employ sandboxing or containerization techniques to isolate the execution environment of the convert_config function, limiting potential damage from code execution. 5) Educate users and developers about the risks of processing untrusted checkpoints and enforce policies restricting such actions. 6) Integrate runtime monitoring and anomaly detection to identify suspicious activities during model conversion or execution. 7) Review and harden access controls to minimize privileges of users performing model conversions, reducing the impact of potential exploitation.

Description

CVE-2025-14927 is a high-severity remote code execution vulnerability in Hugging Face Transformers version 4.57.0, specifically in the convert_config function. It arises from improper validation of user-supplied strings that are executed as Python code, enabling attackers to execute arbitrary code with the privileges of the current user. Exploitation requires user interaction, specifically converting a malicious checkpoint file. The vulnerability impacts confidentiality, integrity, and availability, with a CVSS score of 7.8. There are no known exploits in the wild yet, but the risk is significant due to the widespread use of Hugging Face Transformers in AI and ML workflows. European organizations using this library in development or production environments are at risk, especially those in countries with strong AI sectors. Mitigation involves avoiding untrusted checkpoint files, applying patches once available, and implementing strict input validation and sandboxing.

References

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