The Fix
pip install pydantic==2.4.0
Based on closed pydantic/pydantic issue #11104 · PR/commit linked
@@ -280,14 +280,14 @@ being validated. Some of these arguments have been removed from `@field_validato
```python
-from pydantic import BaseModel, FieldValidationInfo, field_validator
+from pydantic import BaseModel, ValidationInfo, field_validator
repro.py
from typing import Annotated
from pydantic import Field, ValidatorFunctionWrapHandler, WrapValidator
def validate_int(absolute: bool) -> WrapValidator:
def validate(value: Any, handler: ValidatorFunctionWrapHandler) -> int:
validated_value: int = handler(value)
return abs(validated_value) if absolute else validated_value
if absolute:
return WrapValidator(
validate, json_schema_input_type=Annotated[int, Field(json_schema_extra={'absolute': True})]
)
else:
return WrapValidator(validate)
AbsoluteValidator = Annotated[int, validate_int(absolute=True)]
ta = TypeAdapter(AbsoluteValidator)
ta.validate_python(-1)
#> 1
ta.json_schema()
#> {'type': 'integer', 'absolute': True}
verify
Re-run the minimal reproduction on your broken version, then apply the fix and re-run.
fix.md
Option A — Upgrade to fixed release\npip install pydantic==2.4.0\nWhen NOT to use: This fix should not be used if the validator logic relies on the previous behavior of not having `model_type`.\n\n
Why This Fix Works in Production
- Trigger: Currently, `field_name`, `data`, and `model_config` are provided in `ValidationInfo` of field validators, and where applicable have their values.
- Mechanism: The `model_type` was not accessible in validators, limiting their functionality
- Why the fix works: Allows access to `field_name` and `data` in all validators if there is data and a field name, enhancing the functionality of validators in Pydantic. (first fixed release: 2.4.0).
Why This Breaks in Prod
- The `model_type` was not accessible in validators, limiting their functionality
- Production symptom (often without a traceback): Currently, `field_name`, `data`, and `model_config` are provided in `ValidationInfo` of field validators, and where applicable have their values.
Proof / Evidence
- GitHub issue: #11104
- Fix PR: https://github.com/pydantic/pydantic/pull/7542
- First fixed release: 2.4.0
- Reproduced locally: No (not executed)
- Last verified: 2026-02-09
- Confidence: 0.95
- Did this fix it?: Yes (upstream fix exists)
- Own content ratio: 0.55
Discussion
High-signal excerpts from the issue thread (symptoms, repros, edge-cases).
“Just to include a bit more of an easier to read example: On the other hand, the following works because the validator is a class…”
“Even just the applicable FieldInfo from model_fields would be a big help if for any reason the full model_fields is a bridge to far to…”
“Unfortunetly i'm not able to help implement new features, but maybe you can elaborate on why creating PydanticThirdPartyType as BaseModel itself is no solution? Nested…”
“@AdunSG, I simply tried to provide trivial examples here to illustrate what I am asking for”
Failure Signature (Search String)
- Currently, `field_name`, `data`, and `model_config` are provided in `ValidationInfo` of field validators, and where applicable have their values.
Copy-friendly signature
signature.txt
Failure Signature
-----------------
Currently, `field_name`, `data`, and `model_config` are provided in `ValidationInfo` of field validators, and where applicable have their values.
def validate_length(value: Any, info: ValidationInfo):
Error Message
Signature-only (no traceback captured)
error.txt
Error Message
-------------
Currently, `field_name`, `data`, and `model_config` are provided in `ValidationInfo` of field validators, and where applicable have their values.
def validate_length(value: Any, info: ValidationInfo):
Minimal Reproduction
repro.py
from typing import Annotated
from pydantic import Field, ValidatorFunctionWrapHandler, WrapValidator
def validate_int(absolute: bool) -> WrapValidator:
def validate(value: Any, handler: ValidatorFunctionWrapHandler) -> int:
validated_value: int = handler(value)
return abs(validated_value) if absolute else validated_value
if absolute:
return WrapValidator(
validate, json_schema_input_type=Annotated[int, Field(json_schema_extra={'absolute': True})]
)
else:
return WrapValidator(validate)
AbsoluteValidator = Annotated[int, validate_int(absolute=True)]
ta = TypeAdapter(AbsoluteValidator)
ta.validate_python(-1)
#> 1
ta.json_schema()
#> {'type': 'integer', 'absolute': True}
What Broke
Validators failed to access necessary metadata, causing incorrect validation behavior.
Why It Broke
The `model_type` was not accessible in validators, limiting their functionality
Fix Options (Details)
Option A — Upgrade to fixed release Safe default (recommended)
pip install pydantic==2.4.0
When NOT to use: This fix should not be used if the validator logic relies on the previous behavior of not having `model_type`.
Use when you can deploy the upstream fix. It is usually lower-risk than long-lived workarounds.
Fix reference: https://github.com/pydantic/pydantic/pull/7542
First fixed release: 2.4.0
Last verified: 2026-02-09. Validate in your environment.
When NOT to Use This Fix
- This fix should not be used if the validator logic relies on the previous behavior of not having `model_type`.
Verify Fix
verify
Re-run the minimal reproduction on your broken version, then apply the fix and re-run.
Did This Fix Work in Your Case?
Quick signal helps us prioritize which fixes to verify and improve.
Prevention
- Add a CI check that diffs key outputs after upgrades (OpenAPI schema snapshots, JSON payload shapes, CLI output).
- Upgrade behind a canary and run integration tests against the canary before 100% rollout.
- Add a TLS smoke test that performs a real handshake in CI (include CA bundle validation and hostname checks).
- Alert on handshake failures by error string and endpoint to catch cert/CA changes quickly.
Version Compatibility Table
| Version | Status |
|---|---|
| 2.4.0 | Fixed |
Related Issues
No related fixes found.
Sources
We don’t republish the full GitHub discussion text. Use the links above for context.