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🐍 PyPI
Not in CISA KEV
HIGH severity

GHSA-386q-5hp3-95m9 is a high-severity (CVSS 8.8) Code Injection vulnerability in datamodel-code-generator. O3 Security confirms whether GHSA-386q-5hp3-95m9 is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

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

Also known asCVE-2026-54653PYSEC-2026-3555
Published
Jul 28, 2026
Updated
Sep 10, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Sep 10, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • A successful exploit gives an attacker total control of the affected component, not partial access.
  • CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for GHSA-386q-5hp3-95m9.

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs38th percentile — riskier than 38% of all scored CVEsHighest risk
0.00%0.32%0.63%0.95%0.3%0.4%0.4%Aug 26Sep 26Sep 26

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

GHSA-386q-5hp3-95m9 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 372,423 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

Real-World Exposure

1 pkg affected
🐍datamodel-code-generator

Real-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

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

Sinks — extras → generated Python expression:

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

    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).

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

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

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

  3. 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 typeOutput model typeResult
jsonschemapydantic_v2.BaseModelRCE on import
jsonschemadataclasses.dataclassRCE on import
jsonschemamsgspec.StructRCE on import
jsonschematyping.TypedDictsafe (TypedDict doesn't render field(); default_factory silently dropped)
openapipydantic_v2.BaseModelRCE 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)

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIdatamodel-code-generator0.17.0&&< 0.60.20.60.2

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for datamodel-code-generator. 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.

  2. Fix

    Update datamodel-code-generator to 0.60.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-386q-5hp3-95m9 is resolved across your whole dependency graph.

  3. 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.

  4. How O3 protects you

    O3 pinpoints whether GHSA-386q-5hp3-95m9 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-386q-5hp3-95m9. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### 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 proc
O3 Security · Impact-Aware SCA

Is GHSA-386q-5hp3-95m9 in your dependencies?

O3 detects GHSA-386q-5hp3-95m9 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.

GHSA-386q-5hp3-95m9: RCE (High 8.8) | O3 Security