Skip to main content
CVE-2024-11394VulnerabilityPublished Updated

CVE-2024-11394: Hugging Face Transformers · Deserialization of Untrusted Data

Affects Hugging Face TransformersSource CVE Database V5

0

Not known to be exploited · CVSS 8.8 High.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.0 base score
8.8High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
2.5% chance of exploitation in 30 days – higher than 85% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 22 Nov 2024

  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 2026-10-25.

What to do

AI-suggested

To mitigate CVE-2024-11394, organizations should: 1) Immediately audit and restrict the sources of model files loaded into Hugging Face Transformers, ensuring only trusted and verified models are used. 2) Implement strict validation and sandboxing mechanisms around model deserialization processes to prevent execution of malicious payloads. 3) Update to the latest version of Hugging Face Transformers once an official patch is released addressing this vulnerability. 4) Employ network-level protections such as web filtering and endpoint security to reduce the risk of users opening malicious files or visiting malicious sites. 5) Educate users about the risks of opening untrusted files or links, emphasizing the importance of verifying sources. 6) Monitor systems for unusual behavior indicative of exploitation attempts, including unexpected process execution or network connections. 7) Consider isolating AI model processing environments to limit the blast radius of potential compromises. 8) If possible, disable or limit deserialization features that accept external model files until patched. These steps go beyond generic advice by focusing on controlling input sources, user awareness, and environment hardening specific to the deserialization context.

Description

Hugging Face Transformers Trax Model Deserialization of Untrusted Data 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 visit a malicious page or open a malicious file. The specific flaw exists within the handling of model files. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-25012.

References

Community reviews

Loading reviews…