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GHSA-8m8r-38jm-f355
No affected components available
Summary
When the Pydantic v2 output mode is in use, datamodel-code-generator reads a validators array from each model entry in the --extra-template-data file and synthesises a Pydantic @field_validator(...) decorator from each entry. The field names and the validator mode are interpolated into the decorator call wrapped in unescaped single quotes. A value containing ' breaks out of the string literal, letting an attacker emit an arbitrary positional Python expression into the decorator. The expression is evaluated at class-definition time, i.e. the moment the developer imports the generated module. This is the same trust model as the recently-published GHSA-wjv6-jcfj-mf9r (extras-file comment injection) but the impact is full RCE rather than a docstring leak.
Details
Sink: src/datamodel_code_generator/model/pydantic_v2/base_model.py, _process_validators (lines 405–449, at tag 0.60.1 / commit a321547e):
def _process_validators(self) -> None:
validators = self.extra_template_data.get("validators")
if not validators:
return
...
for validator in validators:
fields = validator.get("fields") or [validator.get("field")]
fields = [f for f in fields if f]
if not fields:
continue
function_path: str = validator["function"]
function_name = function_path.rsplit(".", 1)[-1]
mode = validator.get("mode", "after")
fields_str = ", ".join(f"'{f}'" for f in fields) # (A) UNESCAPED
...
mode_str = f"mode='{mode}'" # (B) UNESCAPED
prepared_validators.append({
"fields_str": fields_str,
"mode_str": mode_str,
"method_name": method_name,
"function_name": function_name,
"mode": mode,
})
self._additional_imports.append(Import.from_full_path(function_path)) # (C)
The strings from (A) and (B) flow verbatim into src/datamodel_code_generator/model/template/pydantic_v2/BaseModel.jinja2:
@field_validator({{ v.fields_str }}, {{ v.mode_str }})
There is no repr() call, no identifier check, and no quote-escaping.
Secondary sink at (C): Import.from_full_path(function_path) splits on the last . and emits from <prefix> import <suffix>. A ; in function_path therefore lands in the generated import line and runs as a statement at module load.
PoC
A self-contained one-file PoC is available here: https://gist.github.com/thegr1ffyn/34d5c647e74487ffb2be27c76dace2aa
Impact
Arbitrary code execution in the developer's interpreter / CI runner the moment the generated module is imported. Anyone who accepts a --extra-template-data file from an untrusted source is impacted:
- Pull requests adding or modifying project-local
*.template-data.json/.codegen.jsonfiles consumed by amake codegenrule or pre-commit hook. - Configuration snippets pasted from issue templates, READMEs, or third-party guides.
- Multi-tenant CI systems where one tenant's config file is read by another tenant's build.
Same blast radius as GHSA-wjv6-jcfj-mf9r, but silent RCE rather than a docstring leak — significantly higher impact under the same threat model.
Introduced in 0.52.1 by commit
a2b27562(Add --validators option for Pydantic v2 field validators).
Resolution
The fix validates validators entries with Pydantic models before rendering them. Field names must be valid non-keyword Python identifiers, function must be a dotted Python identifier path, and mode must be one of Pydantic's supported validator modes. The generated decorator arguments now render field names with repr() and mode with !r, so validated values are still emitted as Python string literals.
Remediation
Upgrade to datamodel-code-generator 0.60.2 or later.
This issue affects datamodel-code-generator versions >= 0.52.1, <= 0.60.1 and is fixed in 0.60.2.
Submitted by: Hamza Haroon (thegr1ffyn)
The vulnerability requires local access to the device to be exploited. It is easy for an attacker to exploit this vulnerability. An attacker does not need any special privileges or access rights. The attacker needs the user to perform some action, like clicking a link. The impact is confined to the system where the vulnerability exists. There is a high impact on the confidentiality of the information. There is a high impact on the integrity of the data. There is a high impact on the availability of the system.
Exploitation activity has been observed. Apply available patches or mitigations urgently.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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