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nvd-json-data-feeds/CVE-2021/CVE-2021-295xx/CVE-2021-29510.json
cad-safe-bot 5fc0b01395 Auto-Update: 2024-12-15T03:00:19.262894+00:00
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{
"id": "CVE-2021-29510",
"sourceIdentifier": "security-advisories@github.com",
"published": "2021-05-13T19:15:08.023",
"lastModified": "2024-11-21T06:01:16.707",
"vulnStatus": "Modified",
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Pydantic is a data validation and settings management using Python type hinting. In affected versions passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic."
},
{
"lang": "es",
"value": "Pydantic es un sistema de validaci\u00f3n de datos y gesti\u00f3n de configuraciones que utiliza las sugerencias de tipo de Python. En las versiones afectadas, pasar `'infinity'`, `'inf'` o `float('inf')` (o sus negativos) a los campos `datetime` o `date` hace que la validaci\u00f3n se ejecute eternamente con un uso del 100% de la CPU (en una CPU). Pydantic ha sido parcheado con correcciones disponibles en las siguientes versiones: v1.8.2, v1.7.4, v1.6.2. Todas estas versiones est\u00e1n disponibles en pypi(https://pypi.org/project/pydantic/#history), y estar\u00e1n disponibles en conda-forge(https://anaconda.org/conda-forge/pydantic) pronto. Consulta el registro de cambios(https://pydantic-docs.helpmanual.io/) para m\u00e1s detalles. Si no puedes actualizar absolutamente, puedes evitar este riesgo usando un validador(https://pydantic-docs.helpmanual.io/usage/validators/) para capturar estos valores. Esta no es una soluci\u00f3n ideal (en particular, necesitar\u00e1s una funci\u00f3n ligeramente diferente para las fechas), en lugar de un hack como este deber\u00edas actualizar pydantic. Si no est\u00e1s usando v1.8.x, v1.7.x o v1.6.x y no puedes actualizar a una versi\u00f3n fija de pydantic, por favor crea un issue en https://github.com/samuelcolvin/pydantic/issues solicitando un back-port, y nos esforzaremos en liberar un parche para versiones anteriores de pydantic"
}
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"attackComplexity": "LOW",
"privilegesRequired": "NONE",
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