VAITP

Linuxfabrik monitoring-plugins provides Python monitoring plugins for Icinga, Nagios, and related monitoring systems. In version 6.0.0, the logfile check legacy database migration moved a predictable path from /tmp with os.rename() and allowed a local user controlling the plugin account to place a symlink that would be followed by sqlite3.connect() during a root-run check.

joserfc is a Python library that provides an implementation of several JSON Object Signing and Encryption (JOSE) standards. in versions 1.7.1 and prior, joserfc accepts JWTs with trailing padding (==) which are not conforming to the JOSE specifications. This leads to malleability of the JWTs when consumed by joserfc. Depending on this application this might or not be an issue. This could lead to bypass of token revocation or anti-replay protection when implemented as a deny list of tokens or a deny list of token hashes. Note that ECDSA JWS are always malleable because of the malleability of ECDSA signatures (first test case in the code bellow). This makes a scheme which assumes that JWTs are not malleable brittle. However for other signatures (or MAC) schemes it might make sense to assume non malleability of the token. This issue has been fixed in version 1.7.2.

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 0.11.6 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 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.

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.

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.

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 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.

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.

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.