| Package | Affected versions | Patched versions |
|---|---|---|
| pydantic | ≥ 1.7, < 1.7.4≥ 1.8, < 1.8.2< 1.6.2 | 1.7.41.8.21.6.2 |
| pydantic | ≥ 1.7, < 1.7.4≥ 1.8, < 1.8.2< 1.6.2 | 1.7.41.8.21.6.2 |
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.
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