Описание
Use of "infinity" as an input to datetime and date fields causes infinite loop in pydantic
Impact
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). Patches
Pydantic is be patched with fixes available in the following versions:
All these versions are available on pypi, and will be available on conda-forge soon.
See the changelog for details. Workarounds
If you absolutely can't upgrade, you can work around this risk using a validator to catch these values, brief demo:
from datetime import date from pydantic import BaseModel, validator
class DemoModel(BaseModel): date_of_birth: date
Note: 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 requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic. References
This was fixed in commit 7e83fdd.
Ссылки
- https://github.com/samuelcolvin/pydantic/security/advisories/GHSA-5jqp-qgf6-3pvh
- https://nvd.nist.gov/vuln/detail/CVE-2021-29510
- https://github.com/pydantic/pydantic/commit/1c24f1d74ba95ea985b50bdc001ce96c813229aa
- https://github.com/pydantic/pydantic/commit/80e0dd3f752bef145dce12f160d262bb40ec8d47
- https://github.com/pydantic/pydantic/commit/bdde15b7b947c94ca00fd6eb92da8db390a13520
- https://github.com/samuelcolvin/pydantic/commit/7e83fdd2563ffac081db7ecdf1affa65ef38c468
- https://github.com/pypa/advisory-database/tree/main/vulns/pydantic/PYSEC-2021-47.yaml
- https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/S2HT266L6Q7H6ICP7DFGXOGBJHNNKMKB
- https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/UEFWM7DYKD2ZHE7R5YT5EQWJPV4ZKYRB
- https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/UMKAJX4O6IGBBCE32CO2G7PZQCCQSBLV
Пакеты
pydantic
< 1.6.2
1.6.2
pydantic
>= 1.8, < 1.8.2
1.8.2
pydantic
>= 1.7, < 1.7.4
1.7.4
Связанные уязвимости
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...
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 up
Pydantic is a data validation and settings management using Python typ ...
Уязвимость полей даты средства анализа и проверки данных Pydantic, связанная с выполнением цикла с недоступным условием выхода, позволяющая нарушителю вызвать отказ в обслуживании