CVE-2024-11393
published 2024-11-22CVE-2024-11393: Hugging Face Transformers MaskFormer Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to…
PriorityP357high8.8CVSS 3.1
AVNACLPRNUIRSUCHIHAH
EPSS
2.89%
85.2th percentile
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.
Affected
3 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| hugging_face | transformers | — | — |
| huggingface | transformers | < 4.48.0 | 4.48.0 |
| huggingface | transformers | >= 0 < 4.48.0 | 4.48.0 |
Detection & IOCsextracted from sources · hover to see the quote
- →The vulnerability exists within the parsing of model files in Hugging Face Transformers MaskFormer model — inspect loading of untrusted model files (e.g., pickle-based deserialization) via the MaskFormer model class for arbitrary code execution. ↗
- →User interaction is required; attack vector involves a user visiting a malicious page or opening a malicious file — monitor for suspicious model file downloads or loads from untrusted sources in environments running Hugging Face Transformers. ↗
- →Code executes in the context of the current user — post-exploitation activity should be correlated with the user account running the Transformers/MaskFormer model loading process. ↗
- ·Red Hat Product Security does not consider this a vulnerability for their products; all listed Red Hat/OpenShift packages are marked Not Affected. ↗
- ·No mitigation meeting Red Hat's criteria (ease of use, deployment, applicability, stability) is currently available. ↗
CVSS provenance
nvdv3.18.8HIGHCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
nvdv3.08.8HIGHCVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
vendor_redhat8.8HIGH
Stop checking back — get the weekly exploitation signal.
Every Monday: what got weaponized or added to CISA KEV in the last seven days — each CVE cross-linked to its PoC, Nuclei template, and detection rule. Free, one email a week, unsubscribe in one click.
GHSA
Deserialization of Untrusted Data in Hugging Face Transformers
ghsa·2024-11-23
CVE-2024-11393 [HIGH] CWE-502 Deserialization of Untrusted Data in Hugging Face Transformers
Deserialization of Untrusted Data in Hugging Face Transformers
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.
OSV
Deserialization of Untrusted Data in Hugging Face Transformers
osv·2024-11-23
CVE-2024-11393 [HIGH] Deserialization of Untrusted Data in Hugging Face Transformers
Deserialization of Untrusted Data in Hugging Face Transformers
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.
OSV
CVE-2024-11393: Hugging Face Transformers MaskFormer Model Deserialization of Untrusted Data Remote Code Execution Vulnerability
osv·2024-11-22
CVE-2024-11393 CVE-2024-11393: Hugging Face Transformers MaskFormer Model Deserialization of Untrusted Data Remote Code Execution Vulnerability
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.
Red Hat
transformers: Hugging Face Transformers MaskFormer Model Deserialization of Untrusted Data Remote Code Execution Vulnerability
vendor_redhat·2024-11-22·CVSS 8.8
CVE-2024-11393 [HIGH] CWE-502 transformers: Hugging Face Transformers MaskFormer Model Deserialization of Untrusted Data Remote Code Execution Vulnerability
transformers: Hugging Face Transformers MaskFormer Model Deserialization of Untrusted Data Remote Code Execution Vulnerability
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-25
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
2024-11-22
Published