CVE-2025-24357
VLLM Deserialization Code Execution Vulnerability
Description
vLLM is a library for LLM inference and serving. vllm/model_executor/weight_utils.py implements hf_model_weights_iterator to load the model checkpoint, which is downloaded from huggingface. It uses the torch.load function and the weights_only parameter defaults to False. When torch.load loads malicious pickle data, it will execute arbitrary code during unpickling. This vulnerability is fixed in v0.7.0.
INFO
Published Date :
Jan. 27, 2025, 6:15 p.m.
Last Modified :
Jan. 27, 2025, 6:15 p.m.
Source :
[email protected]
Remotely Exploitable :
Yes !
Impact Score :
5.9
Exploitability Score :
1.6
Affected Products
The following products are affected by CVE-2025-24357
vulnerability.
Even if cvefeed.io is aware of the exact versions of the
products
that
are
affected, the information is not represented in the table below.
No affected product recoded yet
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2025-24357.
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2025-24357 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2025-24357 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
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New CVE Received by [email protected]
Jan. 27, 2025
Action Type Old Value New Value Added Description vLLM is a library for LLM inference and serving. vllm/model_executor/weight_utils.py implements hf_model_weights_iterator to load the model checkpoint, which is downloaded from huggingface. It uses the torch.load function and the weights_only parameter defaults to False. When torch.load loads malicious pickle data, it will execute arbitrary code during unpickling. This vulnerability is fixed in v0.7.0. Added CVSS V3.1 AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H Added CWE CWE-502 Added Reference https://github.com/vllm-project/vllm/commit/d3d6bb13fb62da3234addf6574922a4ec0513d04 Added Reference https://github.com/vllm-project/vllm/pull/12366 Added Reference https://github.com/vllm-project/vllm/security/advisories/GHSA-rh4j-5rhw-hr54 Added Reference https://pytorch.org/docs/stable/generated/torch.load.html
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2025-24357 is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2025-24357
weaknesses.