FKIE_CVE-2026-27893
Vulnerability from fkie_nvd - Published: 2026-03-27 00:16 - Updated: 2026-07-21 12:17
Severity
8.8 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
8.8 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
8.8 (High) - CVSS:3.1/
Summary
vLLM is an inference and serving engine for large language models (LLMs). Starting in version 0.10.1 and prior to version 0.18.0, two model implementation files hardcode `trust_remote_code=True` when loading sub-components, bypassing the user's explicit `--trust-remote-code=False` security opt-out. This enables remote code execution via malicious model repositories even when the user has explicitly disabled remote code trust. Version 0.18.0 patches the issue.
References
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"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c"
}
],
"configurations": [
{
"nodes": [
{
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{
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"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "vLLM is an inference and serving engine for large language models (LLMs). Starting in version 0.10.1 and prior to version 0.18.0, two model implementation files hardcode `trust_remote_code=True` when loading sub-components, bypassing the user\u0027s explicit `--trust-remote-code=False` security opt-out. This enables remote code execution via malicious model repositories even when the user has explicitly disabled remote code trust. Version 0.18.0 patches the issue."
},
{
"lang": "es",
"value": "vLLM es un motor de inferencia y servicio para modelos de lenguaje grandes (LLM). A partir de la versi\u00f3n 0.10.1 y antes de la versi\u00f3n 0.18.0, dos archivos de implementaci\u00f3n de modelos codifican de forma r\u00edgida \u0027trust_remote_code=True\u0027 al cargar subcomponentes, eludiendo la exclusi\u00f3n voluntaria de seguridad expl\u00edcita del usuario \u0027--trust-remote-code=False\u0027. Esto permite la ejecuci\u00f3n remota de c\u00f3digo a trav\u00e9s de repositorios de modelos maliciosos incluso cuando el usuario ha deshabilitado expl\u00edcitamente la confianza en el c\u00f3digo remoto. La versi\u00f3n 0.18.0 corrige el problema."
}
],
"id": "CVE-2026-27893",
"lastModified": "2026-07-21T12:17:51.353",
"metrics": {
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"baseScore": 8.8,
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"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
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"privilegesRequired": "NONE",
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{
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"type": "Secondary"
}
]
}
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model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.