Language: Python
Label: safe
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:
            predict_cmd = [
                "python",
                _mlflow_pyfunc_backend_predict.__file__,
                "--model-uri",
                str(local_uri),
                "--content-type",
                shlex.quote(str(content_type)),
            ]
            if input_path:
                predict_cmd += ["--input-path", shlex.quote(str(input_path))]
            if output_path:
                predict_cmd += ["--output-path", shlex.quote(str(output_path))]
            return self.prepare_env(local_path).execute(" ".join(predict_cmd))
        else:
            scoring_server._predict(local_uri, input_path, output_path, content_type)