Vulnerability-Lookup

CVE-2026-54653 (GCVE-0-2026-54653)

Vulnerability from cvelistv5 – Published: 2026-07-28 21:48 – Updated: 2026-07-29 13:27

Title

`datamodel-code-generator` vulnerable to code injection in via attacker-controlled `default_factory` schema field

Summary

datamodel-code-generator generates Pydantic v2 models, dataclasses, TypedDict, and msgspec.Struct from OpenAPI, JSON Schema, GraphQL, Avro, Protobuf, and raw JSON, YAML, or CSV. From 0.17.0 until 0.60.2, datamodel-code-generator preserves attacker-controlled default_factory values in src/datamodel_code_generator/parser/jsonschema.py through JsonSchemaObject.init and get_field_extras and emits them into Field(default_factory=...) or field(default_factory=...), allowing Python expression execution when the generated model is imported. This issue is fixed in version 0.60.2.

Severity

8.8 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

SSVC

Exploitation: none Automatable: no Technical Impact: total

CISA Coordinator (v2.0.3)

CWE

CWE-94 - Improper Control of Generation of Code ('Code Injection')
CWE-1336 - Improper Neutralization of Special Elements Used in a Template Engine

Assigner

GitHub_M

References

4 references

URL	Tags
https://github.com/koxudaxi/datamodel-code-genera…	x_refsource_CONFIRM
https://github.com/koxudaxi/datamodel-code-genera…	x_refsource_MISC
https://github.com/koxudaxi/datamodel-code-genera…	x_refsource_MISC
https://gist.github.com/thegr1ffyn/9648b0fe4fcf7d…	exploit

Impacted products

1 product

Vendor	Product	Version
koxudaxi	datamodel-code-generator	Affected: >= 0.17.0, < 0.60.2

Show details on NVD website

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GHSA-386Q-5HP3-95M9

Vulnerability from github – Published: 2026-07-28 21:48 – Updated: 2026-07-28 21:48

Summary

`datamodel-code-generator` vulnerable to code injection in via attacker-controlled `default_factory` schema field

Details

Summary

datamodel-code-generator is vulnerable to code injection when generating Python models from an attacker-controlled JSON Schema, OpenAPI, YAML, JSON, Avro, Protobuf, or XSD schema. When a property carries a "default_factory" key, its value is interpolated verbatim — as a raw Python expression — into the generated Field(default_factory=...) / field(default_factory=...) call. Because this assignment is evaluated at class-definition time (i.e. on import of the generated module), an attacker who controls the schema controls a Python expression that runs in the consumer's process. No special CLI flags are required.

Details

The vulnerable chain spans the JSON-Schema-shaped parser and three sink locations (Pydantic v2, dataclass, msgspec):

Source — schema → extras:

src/datamodel_code_generator/parser/jsonschema.py:600-614 — DEFAULT_FIELD_KEYS includes the literal string "default_factory".
src/datamodel_code_generator/parser/jsonschema.py:457-459 — JsonSchemaObject.__init__ stores any non-standard key (including default_factory) in self.extras.
src/datamodel_code_generator/parser/jsonschema.py:797-812 — get_field_extras preserves default_factory through to the field model.

Sinks — extras → generated Python expression:

src/datamodel_code_generator/model/pydantic_base.py:222-249:

python default_factory = data.pop("default_factory", None) ... if default_factory is not None: field_arguments = [f"default_factory={default_factory}", *field_arguments]

The default_factory value is interpolated raw (no repr(), no validation).

src/datamodel_code_generator/model/dataclass.py:211:

python f"{k}={v if k == 'default_factory' else repr(v)}"

Explicit special-case to skip repr() for default_factory.

src/datamodel_code_generator/model/msgspec.py:361 — same pattern as dataclass.

Because default_factory is in DEFAULT_FIELD_KEYS, no special CLI flag is needed to reach the sink. Any input format that uses the JSON-Schema-shaped parser (jsonschema, openapi, yaml, json, dict, csv) — and any input format that converts to it (avro, protobuf, xmlschema) — is in scope.

Confirmed PoC matrix

Input file type	Output model type	Result
`jsonschema`	`pydantic_v2.BaseModel`	RCE on import
`jsonschema`	`dataclasses.dataclass`	RCE on import
`jsonschema`	`msgspec.Struct`	RCE on import
`jsonschema`	`typing.TypedDict`	safe (TypedDict doesn't render `field()`; `default_factory` silently dropped)
`openapi`	`pydantic_v2.BaseModel`	RCE on import

Other JSON-Schema-shaped inputs (yaml, json, dict, csv, avro, protobuf, xmlschema) follow the same code path and are expected to reproduce.

PoC

Self contained Proof of Concept is available at my secret gist: https://gist.github.com/thegr1ffyn/9648b0fe4fcf7d569ac8e61dd11eebaf

Impact

Who's affected: any developer or CI pipeline that runs datamodel-codegen against a schema they didn't author themselves — third-party API specs, schemas pulled from a registry, vendored upstream .json / .yaml / .avsc / .proto / .xsd files, schemas fetched from a remote URL or introspection endpoint — and who imports the generated .py.
What it gains: arbitrary Python code execution in the importer's process at import time. The PoC copies /etc/passwd to a tmp file to demonstrate arbitrary read; the same primitive supports any operation the importing process can perform (filesystem write, environment exfiltration, secondary network calls, RCE on CI runners).
What it does NOT need: no special CLI flags, no custom templates, no --extra-template-data, no --use-schema-description. Default invocation against a malicious schema is sufficient.
What does block it: choosing --output-model-type typing.TypedDict (which doesn't render field() / Field() calls). All other supported output model types are vulnerable.

Resolution

The fix validates schema-provided default_factory values while extracting JSON Schema field extras. Only the supported factory names dict, list, and set are accepted; any other value now raises a generator error before code generation. Generator-created default factories for supported mutable defaults and optional nested models continue to use the existing code paths.

Remediation

Upgrade to datamodel-code-generator 0.60.2 or later.

This issue affects datamodel-code-generator versions >= 0.17.0, <= 0.60.1 and is fixed in 0.60.2.

Submitted by: Hamza Haroon (thegr1ffyn)

Severity

8.8 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Show details on source website

JSON

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      "database_specific": {
        "last_known_affected_version_range": "\u003c= 0.60.1"
      },
      "package": {
        "ecosystem": "PyPI",
        "name": "datamodel-code-generator"
      },
      "ranges": [
        {
          "events": [
            {
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            },
            {
              "fixed": "0.60.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-54653"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1336",
      "CWE-94"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-07-28T21:48:14Z",
    "nvd_published_at": null,
    "severity": "HIGH"
  },
  "details": "### Summary\n\n`datamodel-code-generator` is vulnerable to code injection when generating Python models from an attacker-controlled JSON Schema, OpenAPI, YAML, JSON, Avro, Protobuf, or XSD schema. When a property carries a `\"default_factory\"` key, its value is interpolated verbatim \u2014 as a raw Python expression \u2014 into the generated `Field(default_factory=...)` / `field(default_factory=...)` call. Because this assignment is evaluated at class-definition time (i.e. on `import` of the generated module), an attacker who controls the schema controls a Python expression that runs in the consumer\u0027s process. No special CLI flags are required.\n\n### Details\n\nThe vulnerable chain spans the JSON-Schema-shaped parser and three sink locations (Pydantic v2, dataclass, msgspec):\n\n**Source \u2014 schema \u2192 `extras`**:\n\n- `src/datamodel_code_generator/parser/jsonschema.py:600-614` \u2014 `DEFAULT_FIELD_KEYS` includes the literal string `\"default_factory\"`.\n- `src/datamodel_code_generator/parser/jsonschema.py:457-459` \u2014 `JsonSchemaObject.__init__` stores any non-standard key (including `default_factory`) in `self.extras`.\n- `src/datamodel_code_generator/parser/jsonschema.py:797-812` \u2014 `get_field_extras` preserves `default_factory` through to the field model.\n\n**Sinks \u2014 `extras` \u2192 generated Python expression**:\n\n1. `src/datamodel_code_generator/model/pydantic_base.py:222-249`:\n\n   ```python\n   default_factory = data.pop(\"default_factory\", None)\n   ...\n   if default_factory is not None:\n       field_arguments = [f\"default_factory={default_factory}\", *field_arguments]\n   ```\n\n   The `default_factory` value is interpolated raw (no `repr()`, no validation).\n\n2. `src/datamodel_code_generator/model/dataclass.py:211`:\n\n   ```python\n   f\"{k}={v if k == \u0027default_factory\u0027 else repr(v)}\"\n   ```\n\n   Explicit special-case to skip `repr()` for `default_factory`.\n\n3. `src/datamodel_code_generator/model/msgspec.py:361` \u2014 same pattern as dataclass.\n\nBecause `default_factory` is in `DEFAULT_FIELD_KEYS`, no special CLI flag is needed to reach the sink. Any input format that uses the JSON-Schema-shaped parser (`jsonschema`, `openapi`, `yaml`, `json`, `dict`, `csv`) \u2014 and any input format that converts to it (`avro`, `protobuf`, `xmlschema`) \u2014 is in scope.\n\n### Confirmed PoC matrix\n\n| Input file type | Output model type | Result |\n|---|---|---|\n| `jsonschema` | `pydantic_v2.BaseModel` | RCE on import |\n| `jsonschema` | `dataclasses.dataclass` | RCE on import |\n| `jsonschema` | `msgspec.Struct` | RCE on import |\n| `jsonschema` | `typing.TypedDict` | safe (TypedDict doesn\u0027t render `field()`; `default_factory` silently dropped) |\n| `openapi`    | `pydantic_v2.BaseModel` | RCE on import |\n\nOther JSON-Schema-shaped inputs (`yaml`, `json`, `dict`, `csv`, `avro`, `protobuf`, `xmlschema`) follow the same code path and are expected to reproduce.\n\n### PoC\nSelf contained Proof of Concept is available at my secret gist: https://gist.github.com/thegr1ffyn/9648b0fe4fcf7d569ac8e61dd11eebaf\n\n### Impact\n\n- **Who\u0027s affected**: any developer or CI pipeline that runs `datamodel-codegen` against a schema they didn\u0027t author themselves \u2014 third-party API specs, schemas pulled from a registry, vendored upstream `.json` / `.yaml` / `.avsc` / `.proto` / `.xsd` files, schemas fetched from a remote URL or introspection endpoint \u2014 *and* who imports the generated `.py`.\n- **What it gains**: arbitrary Python code execution in the importer\u0027s process at `import` time. The PoC copies `/etc/passwd` to a tmp file to demonstrate arbitrary read; the same primitive supports any operation the importing process can perform (filesystem write, environment exfiltration, secondary network calls, RCE on CI runners).\n- **What it does NOT need**: no special CLI flags, no custom templates, no `--extra-template-data`, no `--use-schema-description`. Default invocation against a malicious schema is sufficient.\n- **What does block it**: choosing `--output-model-type typing.TypedDict` (which doesn\u0027t render `field()` / `Field()` calls). All other supported output model types are vulnerable.\n\n### Resolution\n\nThe fix validates schema-provided `default_factory` values while extracting JSON Schema field extras. Only the supported factory names `dict`, `list`, and `set` are accepted; any other value now raises a generator error before code generation. Generator-created default factories for supported mutable defaults and optional nested models continue to use the existing code paths.\n\n### Remediation\n\nUpgrade to `datamodel-code-generator` `0.60.2` or later.\n\nThis issue affects `datamodel-code-generator` versions `\u003e= 0.17.0, \u003c= 0.60.1` and is fixed in `0.60.2`.\n\nSubmitted by: Hamza Haroon (thegr1ffyn)",
  "id": "GHSA-386q-5hp3-95m9",
  "modified": "2026-07-28T21:48:14Z",
  "published": "2026-07-28T21:48:14Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/koxudaxi/datamodel-code-generator/security/advisories/GHSA-386q-5hp3-95m9"
    },
    {
      "type": "WEB",
      "url": "https://github.com/koxudaxi/datamodel-code-generator/commit/17fc235e234cbcfaaadef8c74cb72c9687db0d1d"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/koxudaxi/datamodel-code-generator"
    },
    {
      "type": "WEB",
      "url": "https://github.com/koxudaxi/datamodel-code-generator/releases/tag/0.60.2"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "`datamodel-code-generator` vulnerable to code injection in via attacker-controlled `default_factory` schema field"
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.

Action not permitted

CVE-2026-54653 (GCVE-0-2026-54653)

GHSA-386Q-5HP3-95M9

Summary

Details

Confirmed PoC matrix

PoC

Impact

Resolution

Remediation

Tags

Sightings

Nomenclature