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:

• v1.8.2
• v1.7.4
• v1.6.2

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

    @validator('date_of_birth', pre=True)
    def skip_infinite_values(cls, v):
        try:
            seconds = float(v)
        except (ValueError, TypeError):
            return v
        else:
            if seconds == float('inf'):
                return date.max
            elif seconds == float('-inf'):
                return date.min
            else:
                return seconds

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.