CVE intelligence and bounded remediation

CVE-2025-66448 — vLLM is an inference and serving engine for large language models (LLMs)

High CVSS 8.8

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.

Severity
High
CVSS
8.8 (3.1)
Published
2025-12-01
CISA KEV
Not currently listed
Ecosystem
python/pypi
Weaknesses
CWE-94

Affected products

  • vllm / vllm

Matched remediation archetype

Command, code, expression, and template injection

This catalog composition supplies bounded fallback guidance. Explicitly reviewed curated workflows load with the complete record below.

Check exposure

  • Trace untrusted values to process execution, interpreters, evaluators, template engines, dynamic imports, and administrative scripting features.
  • Determine whether the affected path is reachable across each trust boundary and which service account or host privilege it inherits.
  • Review configuration for optional execution features, unsafe compatibility modes, and shell invocation.

Remediate safely

  • Replace string-built commands or evaluated code with fixed operations and structured argument APIs that do not invoke a shell.
  • Use strict allowlists for operation identifiers and reject unexpected input before it reaches any interpreter.
  • Update the affected component and add inert regression tests covering metacharacters, encoding variants, and alternate request paths.

Authoritative sources

Complete CVE record and remediation plan

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