CVE-2024-11392: Hugging Face Transformers · Deserialization of Untrusted Data
Affects Hugging Face TransformersSource CVE Database V5
Not known to be exploited · public exploit available (Exploit-DB) · CVSS 7.5 High.
Data as of 25 Oct 2026, 19:02 UTC
- EPSS
- 7.2% chance of exploitation in 30 days – higher than 94% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:HExploitation evidence
t = 0 is the CVE’s publication on cve.org
Disclosed: evidence found.
CVE published 22 Nov 2024
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: evidence found.
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
Timeline
CVE ID reserved
by zdi
, 4 days before disclosure
CVE published
on cve.org
, t = 0
First Exploit-DB entry (opens in a new tab)
Hugging Face Transformers MobileViTV2 4.41.1 - Remote Code Execution (RCE)
, 145 days after disclosure
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
1. Immediately audit and restrict the sources of configuration files and other inputs processed by Hugging Face Transformers to trusted origins only. 2. Implement strict input validation and sanitization for all user-supplied data before deserialization. 3. Employ application-level sandboxing or containerization to limit the impact of potential code execution. 4. Monitor systems for unusual activity indicative of exploitation attempts, such as unexpected process spawning or network connections. 5. Educate users about the risks of opening files or visiting links from untrusted sources, especially in environments using the vulnerable library. 6. Track updates from Hugging Face for official patches or security advisories and apply them promptly once available. 7. Consider using runtime application self-protection (RASP) or endpoint detection and response (EDR) tools to detect and block exploitation attempts. 8. Review and harden access controls around AI/ML infrastructure to minimize the privileges of processes running the Transformers library.
Description
Hugging Face Transformers MobileViTV2 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 configuration 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-24322.