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CVE-2025-1194

Estado: AnalizadaMedia (6.5)—

A Regular Expression Denial of Service (ReDoS) vulnerability was identified in the huggingface/transformers library, specifically in the file `tokenization_gpt_neox_japanese.py` of the GPT-NeoX-Japanese model. The vulnerability occurs in the SubWordJapaneseTokenizer class, where regular expressions process specially crafted inputs. The issue stems from a regex exhibiting exponential complexity under certain conditions, leading to excessive backtracking. This can result in high CPU usage and potential application downtime, effectively creating a Denial of Service (DoS) scenario. The affected version is v4.48.1 (latest).

CVSS

Probabilidad de explotación (EPSS)

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).

Tecnologías afectadas (1)

Huggingface — Transformers

CWE

Referencias

JSON original (NVD)

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  "id": "CVE-2025-1194",
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          "version": "2.0.3",
          "timestamp": "2025-04-29T13:21:09.310802Z"
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  "published": "2025-04-29T12:15:31.717",
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          "value": "CWE-1333"
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  "descriptions": [
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      "value": "A Regular Expression Denial of Service (ReDoS) vulnerability was identified in the huggingface/transformers library, specifically in the file `tokenization_gpt_neox_japanese.py` of the GPT-NeoX-Japanese model. The vulnerability occurs in the SubWordJapaneseTokenizer class, where regular expressions process specially crafted inputs. The issue stems from a regex exhibiting exponential complexity under certain conditions, leading to excessive backtracking. This can result in high CPU usage and potential application downtime, effectively creating a Denial of Service (DoS) scenario. The affected version is v4.48.1 (latest)."
    },
    {
      "lang": "es",
      "value": "Se identificó una vulnerabilidad de denegación de servicio por expresión regular (ReDoS) en la librería huggingface/transformers, concretamente en el archivo `tokenization_gpt_neox_japanese.py` del modelo GPT-NeoX-Japanese. La vulnerabilidad se produce en la clase SubWordJapaneseTokenizer, donde las expresiones regulares procesan entradas especialmente manipuladas. El problema se debe a que una expresión regular presenta una complejidad exponencial en determinadas condiciones, lo que provoca un retroceso excesivo. Esto puede provocar un alto consumo de CPU y un posible tiempo de inactividad de la aplicación, creando así un escenario de denegación de servicio (DoS). La versión afectada es la v4.48.1 (última versión)."
    }
  ],
  "lastModified": "2026-06-17T08:38:34.587",
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