CVE-2025-14926: Hugging Face Transformers · Code Injection
Affects Hugging Face TransformersSource CVE Database V5
Not known to be exploited · CVSS 7.8 High.
Data as of 25 Oct 2026, 19:02 UTC
- 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:HExploitation evidence
Disclosed: evidence found.
CVE published 23 Dec 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by 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 2026-10-25.
What to do
Affected software
| Product | Affected | Fixed in |
|---|---|---|
PyPItransformerspkg:pypi/transformersOther threats | Affected
| Fixed in– |
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
1. Avoid converting or loading checkpoint files from untrusted or unknown sources to prevent triggering the vulnerability. 2. Implement strict input validation and sanitization for any user-supplied configuration data before processing. 3. Use sandboxing or containerization techniques to isolate the execution environment of model conversion processes, limiting potential damage from code execution. 4. Monitor and audit logs for unusual activities related to model conversion or checkpoint processing. 5. Stay updated with Hugging Face releases and apply patches promptly once available. 6. Educate users and developers about the risks of processing untrusted model files and enforce policies restricting such actions. 7. Consider employing application whitelisting or endpoint protection solutions that can detect and block suspicious code execution patterns related to this vulnerability.
Description
CVE-2025-14926 is a high-severity code injection vulnerability in Hugging Face Transformers version 4.57.0, specifically in the convert_config function. It allows remote attackers to execute arbitrary Python code by supplying a malicious checkpoint configuration. Exploitation requires user interaction, as the target must convert a crafted checkpoint file. The vulnerability arises from improper validation of user-supplied strings before execution, enabling code execution with the privileges of the current user. Although no known exploits are currently in the wild, the impact on confidentiality, integrity, and availability is high. This vulnerability poses a significant risk to organizations using Hugging Face Transformers for machine learning model management or deployment. European organizations relying on this library, especially in AI research and development sectors, should prioritize patching or mitigating this issue. Countries with strong AI and tech industries, such as Germany, France, the UK, and the Netherlands, are likely to be most affected.