CVE-2025-62164: vllm Input Validation Flaw — Fix

Description

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.

Is your site exposed to CVE-2025-62164?

Run a free security scan — no signup, results in seconds.

CVSS v3.1 Score

8.8

HIGH

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Weakness Type (CWE)

CWE-20 Improper Input Validation

CWE-123 CWE-123

CWE-502 Deserialization of Untrusted Data

CWE-787 Out-of-bounds Write

Affected Products

Vendor	Product	Versions
vllm	vllm	0.10.2 — 0.11.1
vllm	vllm	All
vllm	vllm	All

References

Advisories & Patches

https://github.com/vllm-project/vllm/commit/58fab50d82838d5014f4a14d991fdb9352c9c84b https://github.com/vllm-project/vllm/pull/27204 https://github.com/vllm-project/vllm/security/advisories/GHSA-mrw7-hf4f-83pf

Frequently Asked Questions

What is CVE-2025-62164? +

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. It has a CVSS v3.1 base score of 8.8 (HIGH).

How severe is CVE-2025-62164? +

CVE-2025-62164 has a CVSS v3.1 score of 8.8 out of 10, rated HIGH. This is a high-severity vulnerability that should be prioritized for patching.

What products are affected by CVE-2025-62164? +

CVE-2025-62164 affects products from vllm, specifically: vllm. Check the affected products table above for specific version ranges.

How do I check if I'm vulnerable to CVE-2025-62164? +

You can use Secably's free Website Scanner to check your website for known vulnerabilities. For infrastructure scanning, use the Port Scanner to identify exposed services that may be affected. Check the vendor advisories linked above for specific patch and version information.

Related Vulnerabilities

CVE-2025-13826

Zervit's portable HTTP/web server is vulnerable to remote DoS attacks when a configuration reset request is made. The vulnerability is …

CVE-2024-54011

Penetration Testing engineers at Amazon have discovered a flaw where the camera system fails to properly handle data supplied in …

CVE-2026-6409

A Denial of Service (DoS) vulnerability exists in the Protobuf PHP library during the parsing of untrusted input. Maliciously structured …

CVE-2026-12569

A critical remote code execution (RCE) vulnerability has been reported in PTC Windchill PDMlink and PTC FlexPLM. The vulnerability may …

CVE-2026-0282

A file deletion vulnerability in Palo Alto Networks PAN-OS® software enables an unauthenticated attacker with network access to the management …

CVE-2025-23202

Bible Module is a tool designed for ROBLOX developers to integrate Bible functionality into their games. The `FetchVerse` and `FetchPassage` …

CVE-2025-62164