CVE-2025-62164

🔴 HIGH

vLLM is an inference and serving engine for large language models (LLMs). From versions 0.10.2 to before 0.11.1, a memory corruption vulnerability could lead to a crash (denial-of-service) and potenti...

Published
Nov 21, 2025
Last Modified
Nov 21, 2025
Views
5
Bookmarks
0

vLLM is an inference and serving engine for large language models (LLMs). From versions 0.10.2 to before 0.11.1, a memory corruption vulnerability could lead to a crash (denial-of-service) and potentially remote code execution (RCE), exists in the Completions API endpoint. When processing user-supplied prompt embeddings, the endpoint loads serialized tensors using torch.load() without sufficient validation. Due to a change introduced in PyTorch 2.8.0, sparse tensor integrity checks are disabled by default. As a result, maliciously crafted tensors can bypass internal bounds checks and trigger an out-of-bounds memory write during the call to to_dense(). This memory corruption can crash vLLM and potentially lead to code execution on the server hosting vLLM. This issue has been patched in version 0.11.1.

CVSS Scores

CVSS 3.1 8.8
8.8
HIGH
CVSS 2.0 8.8

Additional Information

Source
security-advisories@github.com
State
Undergoing analysis

Share CVE-2025-62164

Share on Social Media

Copy Link

Embed Code

Request Expert Analysis

Request a professional security analysis for CVE-2025-62164 from our verified experts.

Credits System

Use your credits to get expert analysis from verified security professionals. Purchase more credits anytime!

Add 3 credits for accelerated delivery

Base Cost: 8 credits
Priority Upgrade: + credits
SLA Acceleration: +3 credits
Total Cost:
Your Balance:

Insufficient Credits

You need more credits to submit this request.

Buy Credits

Report Analysis