VAITP Dataset

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Total vulnerabilities in the dataset (not showing ignored and non-python related vulnerabilties): 1787
2178
datamodel-code-generator leaks credentials during cross-origin redirects.

datamodel-code-generator generates Python data models from schema definitions. Prior to 0.63.0, src/datamodel_code_generator/http.py get_body reuses Authorization, Cookie, and Proxy-Authorization headers when following cross-origin redirects while fetching remote schemas, allowing credentials scoped to one schema host to be leaked to another redirect target. This issue is fixed in version 0.63.0.

Checking
Information Leakage
Information Disclosure
Remote
2177
Path traversal in XML schema parsing allows arbitrary local file read.

datamodel-code-generator generates Python data models from schema definitions. From 0.59.0 until 0.62.0, XML Schema parsing in src/datamodel_code_generator/parser/xmlschema.py for --input-file-type xmlschema resolves xs:include, xs:import, xs:redefine, and xs:override schemaLocation values outside the input base path, allowing arbitrary local files to be read and reflected into generated models. This issue is fixed in version 0.62.0.

Checking
Input Validation and Sanitization
Path Traversal
Local
2176
SSRF vulnerability in datamodel-code-generator via unvalidated URL targets.

datamodel-code-generator generates Python data models from schema definitions. From 0.9.1 until 0.61.0, src/datamodel_code_generator/http.py http.get_body accepts --url targets and redirect chain targets without host/IP validation, allowing server-side request forgery against loopback, private, link-local, metadata, and other network-accessible resources. This issue is fixed in version 0.61.0.

Checking
Input Validation and Sanitization
Server-Side Request Forgery (SSRF)
Remote
2175
datamodel-code-generator allows code execution via --extra-template-data.

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.

Checking
Input Validation and Sanitization
Command Injection
Local
2174
Code injection in datamodel-code-generator via malicious x-python-type.

datamodel-code-generator generates Python data models from schema definitions. From 0.51.0 until 0.60.2, x-python-type values parsed by src/datamodel_code_generator/parser/jsonschema.py in _get_python_type_override are inserted into generated field annotations without sufficient validation, allowing attacker-controlled JSON Schema content to execute Python code when the generated module is imported. This issue is fixed in version 0.60.2.

Checking
Input Validation and Sanitization
Command Injection
Local
2173
Improper neutralization of carriage returns in comments allows code injection.

datamodel-code-generator generates Python data models from schema definitions. From 0.14.1 until 0.60.2, the --extra-template-data comment field is rendered into Python comments in src/datamodel_code_generator/model/template/TypeAliasAnnotation.jinja2, src/datamodel_code_generator/model/template/TypedDict.jinja2, src/datamodel_code_generator/model/template/dataclass.jinja2, src/datamodel_code_generator/model/template/msgspec.Struct.jinja2, src/datamodel_code_generator/model/template/pydantic/BaseModel.jinja2, and src/datamodel_code_generator/model/template/pydantic_v2/BaseModel.jinja2 without neutralizing carriage returns in Python # comments, allowing an attacker-controlled comment value to inject Python code into generated models that runs when imported. This issue is fixed in version 0.60.2.

Checking
Input Validation and Sanitization
Command Injection
Local
2172
datamodel-code-generator code injection via unsanitized `default_factory`.

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.

Checking
Input Validation and Sanitization
Command Injection
Local
2171
Unsanitized carriage returns in GraphQL descriptions allow code injection.

datamodel-code-generator generates Python data models from schema definitions. Prior to 0.60.1, GraphQL Union description values in src/datamodel_code_generator/model/template/UnionTypeStatement.jinja2 and src/datamodel_code_generator/model/template/UnionTypeStatement.py312.jinja2 are rendered into Python comments without neutralizing carriage returns in Python # comments, allowing attacker-controlled GraphQL schema content to inject Python code into generated models that runs when imported. This issue is fixed in version 0.60.1.

Checking
Input Validation and Sanitization
Command Injection
Local
2170
pytonapi webhook authentication is bypassed when using a custom path.

pytonapi is a Python SDK for TONAPI that provides REST API, streaming, and webhook access to the TON blockchain. From 2.0.0 to 2.2.0, TonapiWebhookDispatcher fails to validate the Authorization header when a webhook handler is registered with the documented path argument, because setup() stores bearer tokens only under the default suffix paths and never adds the custom path to the token map, so self._tokens.get(path) returns None and the authentication guard is skipped. An unauthenticated remote attacker can POST forged payloads to the custom webhook endpoint and trigger victim-defined handlers. This issue is fixed in version 2.2.1.

Checking
Authentication, Authorization, and Session Management
Insecure Authentication Mechanisms
Remote
2169
HTTP request smuggling in Rouille via line feed injection bypasses controls.

Rouille 0.3.3 through 3.6.2 contains an HTTP request smuggling vulnerability that allows remote attackers to bypass access controls by injecting bare line feed characters (0x0A) into client-supplied request header values that are copied verbatim to upstream connections without validation. Attackers can craft a header value containing a complete additional HTTP request that is interpreted as a separate request by backends such as Go net/http and Python http.server, causing the backend to process a smuggled request with attacker-chosen method, path, and headers that bypasses the rouille handler's access control logic.

Checking
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
Introducing the "VAITP dataset": a specialized repository of Python vulnerabilities and patches, meticulously compiled for the use of the security research community. As Python's prominence grows, understanding and addressing potential security vulnerabilities become crucial. Crafted by and for the cybersecurity community, this dataset offers a valuable resource for researchers, analysts, and developers to analyze and mitigate the security risks associated with Python. Through the comprehensive exploration of vulnerabilities and corresponding patches, the VAITP dataset fosters a safer and more resilient Python ecosystem, encouraging collaborative advancements in programming security.

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Sun Tzu – “The Art of War”

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