GHSA-5jqp-qgf6-3pvh
LOWGHSA-5jqp-qgf6-3pvh is a low-severity (CVSS 3.3) CWE-835 vulnerability in pydantic. O3 Security confirms whether GHSA-5jqp-qgf6-3pvh is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.
Use of "infinity" as an input to datetime and date fields causes infinite loop in pydantic
Blast Radius
pydantic🐍pydantic🐍pydanticReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
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.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | pydantic | all versions | 1.6.2 |
| 🐍PyPI | pydantic | ≥ 1.8&&< 1.8.2 | 1.8.2 |
| 🐍PyPI | pydantic | ≥ 1.7&&< 1.7.4 | 1.7.4 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for pydantic. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update pydantic to 1.6.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-5jqp-qgf6-3pvh is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-5jqp-qgf6-3pvh is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-5jqp-qgf6-3pvh. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-5jqp-qgf6-3pvh in your dependencies?
O3 detects GHSA-5jqp-qgf6-3pvh across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.