CVE-2025-66448HIGH 8.8EPSS p41.9%

CVE-2025-66448CVE-2025-66448

Description

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.11.1, vllm has a critical remote code execution vector in a config class named Nemotron_Nano_VL_Config. When vllm loads a model config that contains an auto_map entry, the config class resolves that mapping with get_class_from_dynamic_module(...) and immediately instantiates the returned class. This fetches and executes Python from the remote repository referenced in the auto_map string. Crucially, this happens even when the caller explicitly sets trust_remote_code=False in vllm.transformers_utils.config.get_config. In practice, an attacker can publish a benign-looking frontend repo whose config.json points via auto_map to a separate malicious backend repo; loading the frontend will silently run the backend’s code on the victim host. This vulnerability is fixed in 0.11.1.

Scoring

CVSS 3.18.8 (HIGH)
VectorCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
EPSS0.56% probability of exploitation · percentile 41.9% · 2026-06-18T12:00:27Z
Published2025-12-01
Last modified2025-12-03

Underlying weaknesses· 1

CWE-94

References

  1. https://github.com/vllm-project/vllm/commit/ffb08379d8870a1a81ba82b72797f196838d0c86
  2. https://github.com/vllm-project/vllm/pull/28126
  3. https://github.com/vllm-project/vllm/security/advisories/GHSA-8fr4-5q9j-m8gm

1

TypeTargetConfidenceTier
WeaknessImproper Control of Generation of Code ('Code Injection')cwe-940%live

Related by meaning· 6

Nearest entities by semantic similarity across the cs-graph corpus.

CVE
CVE-2026-22807
CVE
CVE-2026-27893
CVE
CVE-2025-62164
CVE
CVE-2025-32444
CVE
CVE-2025-24357
CVE
CVE-2026-5241
Sourced from NVD + FIRST.org EPSS. Curated for EU compliance use cases by Adam Lundqvist, Founder at SQUR.