GHSA-5jqp-qgf6-3pvh

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): dateofbirth: 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.