Language: Python
Label: vulnerable
CWE: CWE-78 \u2014 Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')
The product constructs all or part of an OS command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended OS command when it is sent to a downstream component.

Code:
    def predict(self, model_uri, input_path, output_path, content_type):
        """
        Generate predictions using generic python model saved with MLflow. The expected format of
        the input JSON is the Mlflow scoring format.
        Return the prediction results as a JSON.
        """
        local_path = _download_artifact_from_uri(model_uri)
        # NB: Absolute windows paths do not work with mlflow apis, use file uri to ensure
        # platform compatibility.
        local_uri = path_to_local_file_uri(local_path)

        if self._env_manager != _EnvManager.LOCAL:
            command = (
                'python -c "from mlflow.pyfunc.scoring_server import _predict; _predict('
                "model_uri={model_uri}, "
                "input_path={input_path}, "
                "output_path={output_path}, "
                "content_type={content_type})"
                '"'
            ).format(
                model_uri=repr(local_uri),
                input_path=repr(input_path),
                output_path=repr(output_path),
                content_type=repr(content_type),
            )
            return self.prepare_env(local_path).execute(command)
        else:
            scoring_server._predict(local_uri, input_path, output_path, content_type)