CVE-2025-14922: Hugging Face Diffusers · Deserialization of Untrusted Data
Affects Hugging Face DiffusersSource CVE Database V5
Not known to be exploited · CVSS 7.8 High.
Data as of 26 Oct 2026, 14:05 UTC
- EPSS
- 0.3% chance of exploitation in 30 days – higher than 30% 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 26 Oct 2026.
What to do
AI-suggested
- Avoid loading checkpoint files from untrusted or unauthenticated sources to prevent malicious payloads.
- Monitor Hugging Face’s official channels for patches or updates addressing this vulnerability and apply them promptly once available.
- Implement strict input validation and sanitization for all data processed by AI/ML pipelines, especially serialized objects like checkpoints.
- Use sandboxing or containerization to isolate AI model execution environments, limiting the impact of potential code execution.
- Educate users and developers about the risks of opening untrusted files or visiting suspicious links related to AI tools.
- Employ endpoint detection and response (EDR) solutions to detect anomalous behaviors indicative of exploitation attempts.
- Review and restrict permissions of processes running AI workloads to minimize the scope of potential compromise.
- Conduct regular security assessments and code reviews focusing on deserialization and input handling in AI frameworks.
Description
Hugging Face Diffusers CogView4 Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Diffusers. 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 checkpoints. 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 process. Was ZDI-CAN-27424.