Focus on koxudaxi vulnerabilities and metrics.
Last updated: 13 Oct 2026, 22:25 UTC
This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with koxudaxi. We track both calendar-based metrics (using fixed periods) and rolling metrics (using gliding windows) to give you a comprehensive view of security trends and risk evolution. Use these insights to assess risk and plan your patching strategy.
For a broader perspective on cybersecurity threats, explore the comprehensive list of CVEs by vendor and product. Stay updated on critical vulnerabilities affecting major software and hardware providers.
Total koxudaxi CVEs: 6
Earliest CVE date: 28 Jul 2026, 22:17 UTC
Latest CVE date: 28 Jul 2026, 22:17 UTC
Latest CVE reference: CVE-2026-55415
30-day Count (Rolling): 0
365-day Count (Rolling): 6
Calendar-based Variation
Calendar-based Variation compares a fixed calendar period (e.g., this month versus the same month last year), while Rolling Growth Rate uses a continuous window (e.g., last 30 days versus the previous 30 days) to capture trends independent of calendar boundaries.
Month Variation (Calendar): 0%
Year Variation (Calendar): 0%
Month Growth Rate (30-day Rolling): 0.0%
Year Growth Rate (365-day Rolling): 0.0%
Average CVSS: 0.0
Max CVSS: 0
Critical CVEs (≥9): 0
| Range | Count |
|---|---|
| 0.0-3.9 | 6 |
| 4.0-6.9 | 0 |
| 7.0-8.9 | 0 |
| 9.0-10.0 | 0 |
These are the five CVEs with the highest CVSS scores for koxudaxi, sorted by severity first and recency.
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 0.11.6 until 0.64.0, datamodel-code-generator allows attacker-controlled x-python-import or customTypePath schema extensions to reach src/datamodel_code_generator/parser/jsonschema.py and generated import handling through Import.from_full_path and Imports.create_line in src/datamodel_code_generator/imports.py, allowing a newline to break out of an import statement and execute Python code when the generated model is imported. This issue is fixed in version 0.64.0.
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. Prior to 0.63.0, datamodel-code-generator validates a URL host once in src/datamodel_code_generator/http.py through get_body, _validate_url_for_fetch, and _get_ips_from_host, but then lets httpx resolve the host again for the connection, allowing DNS rebinding to bypass allow_private_network=False and reach internal services. This issue is fixed in version 0.63.0.
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. Prior to 0.62.0, datamodel-code-generator resolves JSON Schema $ref targets in src/datamodel_code_generator/parser/jsonschema.py through is_url and _get_ref_body without containing file:// or ../ traversal references to the input directory and without honoring --no-allow-remote-refs, allowing arbitrary local file reads. This issue is fixed in version 0.62.0.
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 0.9.1 until 0.61.0, datamodel-code-generator silently dereferences attacker-controlled JSON Schema $ref HTTP or HTTPS URLs in src/datamodel_code_generator/parser/jsonschema.py through _get_ref_body, and the --allow-remote-refs gate can warn instead of blocking, allowing server-side request forgery through src/datamodel_code_generator/http.py. This issue is fixed in version 0.61.0.
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 0.52.1 until 0.60.2, datamodel-code-generator interpolates validators from --extra-template-data in src/datamodel_code_generator/model/pydantic_v2/base_model.py through _process_validators into @field_validator decorators without safe validation, allowing Python code execution when the generated Pydantic v2 model is imported. This issue is fixed in version 0.60.2.
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.