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VulnerabilityPublished Updated

CVE-2024-11393: 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 26 Oct 2026, 14:05 UTC

CVSS 3.0 base score
8.8High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
3.0% chance of exploitation in 30 days – higher than 87% 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 26 Oct 2026.

What to do

AI-suggested

  1. Immediately restrict the loading of model files to trusted sources only; avoid loading models from unverified or user-supplied inputs.
  2. Implement strict validation and sanitization of all model files before deserialization, including checksum verification and format validation.
  3. Employ sandboxing or containerization to isolate the execution environment of model loading processes, limiting the impact of potential code execution.
  4. Monitor user interactions that involve loading external model files and educate users about the risks of opening untrusted files or links.
  5. Stay updated with Hugging Face security advisories and apply patches or updates as soon as they become available.
  6. Consider using application-level allowlists for model files and disable or restrict deserialization features if not required.
  7. Employ runtime detection tools that can identify anomalous behavior indicative of exploitation attempts.
  8. Review and harden access controls and privilege levels for users and services running the Transformers library to minimize damage from potential exploits.

Description

Hugging Face Transformers MaskFormer 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 parsing 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-25191.

References

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