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SCA: security update for vllm (GHSA-mrw7-hf4f-83pf)

high Tenable Cloud Security Plugin ID 436130

Description

There are packages installed that are affected by a vulnerability referenced in the following CVE:

 - 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. (CVE-2025-62164)

See Also

https://github.com/advisories/GHSA-mrw7-hf4f-83pf

Plugin Details

Severity: High

ID: 436130

Version: Revision 1.9

Type: Local

Family: SCA Checks

Published: 11/21/2025

Updated: 7/2/2026

Supported Sensors: Tenable Cloud Security, Tenable Self-Hosted Container Security

Risk Information

VPR

Risk Factor: Medium

Score: 6.9

Percentile: 96.95

Vendor

Vendor Severity: High

CVSS v2

Risk Factor: High

Base Score: 9

Temporal Score: 6.7

Vector: CVSS2#AV:N/AC:L/Au:S/C:C/I:C/A:C

CVSS Score Source: CVE-2025-62164

CVSS v3

Risk Factor: High

Base Score: 8.8

Temporal Score: 7.7

Vector: CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Temporal Vector: CVSS:3.0/E:U/RL:O/RC:C

Vulnerability Information

Exploit Ease: No known exploits are available

Patch Publication Date: 11/20/2025

Vulnerability Publication Date: 11/20/2025

Reference Information

CVE: CVE-2025-62164