CVE-2026-5241

Estado: ModificadaCrítica (9.6)—
A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The issue arises because the `trust_remote_code` parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path.
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Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `LightGlueConfig` reads the `trust_remote_code` value from the untrusted `config.json` file and propagates it into nested `AutoConfig.from_pretrained()` calls. This results in the execution of attacker-provided Python modules, even when the victim explicitly disables remote code execution. The vulnerability poses a high risk for environments such as API inference servers, research notebooks, CI/CD pipelines, and model evaluation workers, potentially leading to credential theft, lateral movement, or persistence/backdoor deployment.
CVSS

Versión: 3.1
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H
Puntuación base: 9.6
Probabilidad de explotación (EPSS)

Probabilidad de explotación en los próximos 30 días: 0.94%
Percentil entre todas las CVEs puntuadas: 59
Fecha de la puntuación: 4/10/2026
EPSS (Exploit Prediction Scoring System, de FIRST) estima la probabilidad de que una vulnerabilidad sea explotada en 30 días. Complementa a CVSS (impacto) y a CISA KEV (explotación confirmada).
🎯 Técnicas ATT&CK

Cómo se explota esta vulnerabilidad y qué consigue el atacante, en el lenguaje de MITRE ATT&CK.
ExplotaciónT1203 Exploitation for Client Executionexecution95 %
Impacto principalT1059 Command and Scripting Interpreterexecution90 %
Impacto secundarioT1136.003 Cloud Accountpersistence60 %
Impacto secundarioT1552.007 Container APIcredential access75 %
Explotación T1203: requiere interacción del usuario (UI:R) al cargar modelo con from_pretrained(). Impactos: ejecución de código Python arbitrario en inicialización del modelo, robo de credenciales en entornos de servidores inference/notebooks, y potencial creación de cuentas para persistencia/backd
Inferido por nuestro agente de análisis a partir de la descripción oficial, el vector CVSS y la CWE, y comprobado por un supervisor. Puede contener errores.
🛡️ Mitigaciones ATT&CK que cubren estas técnicas

Privileged Account Management Network Segmentation User Account Management Restrict Web-Based Content Multi-factor Authentication Limit Software Installation
Tecnologías afectadas (1)

Huggingface — Transformers
CWE

CWE-829
CWE-829
Referencias

JSON original (NVD)

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      "source": "security@huntr.dev",
      "description": [
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          "value": "CWE-829"
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      "value": "A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The issue arises because the `trust_remote_code` parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `LightGlueConfig` reads the `trust_remote_code` value from the untrusted `config.json` file and propagates it into nested `AutoConfig.from_pretrained()` calls. This results in the execution of attacker-provided Python modules, even when the victim explicitly disables remote code execution. The vulnerability poses a high risk for environments such as API inference servers, research notebooks, CI/CD pipelines, and model evaluation workers, potentially leading to credential theft, lateral movement, or persistence/backdoor deployment."
    },
    {
      "lang": "es",
      "value": "Una vulnerabilidad en la ruta de carga del modelo LightGlue de huggingface/transformers versión 5.2.0 permite que un repositorio de modelos controlado por un atacante ejecute código arbitrario durante la inicialización del modelo. El problema surge porque el parámetro 'trust_remote_code', destinado a prevenir la ejecución remota de código, es sobrescrito por datos de configuración serializados no confiables en una ruta de código anidada. Específicamente, al cargar un modelo LightGlue usando 'AutoModel.from_pretrained()' con 'trust_remote_code=False', el 'LightGlueConfig' lee el valor de 'trust_remote_code' del archivo 'config.json' no confiable y lo propaga a llamadas anidadas de 'AutoConfig.from_pretrained()'. Esto resulta en la ejecución de módulos Python proporcionados por el atacante, incluso cuando la víctima deshabilita explícitamente la ejecución remota de código. La vulnerabilidad representa un alto riesgo para entornos como servidores de inferencia de API, notebooks de investigación, pipelines de CI/CD y workers de evaluación de modelos, lo que podría llevar al robo de credenciales, movimiento lateral o despliegue de persistencia/puerta trasera."
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  "lastModified": "2026-08-28T16:18:18.957",
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