Follow-up for Model object introduction

modelscan/modelscan.py

@@ -161,9 +161,10 @@ def scan(
 
         if self._skipped:
             all_skipped_paths = [skipped.source for skipped in self._skipped]
-            for skipped in self._skipped:
-                main_file_path = skipped.source.split(":")[0]
-                if main_file_path == skipped.source:
+            for path in all_paths:
+                main_file_path = str(path).split(":")[0]
+
+                if main_file_path == str(path):
                     continue
 
                 # If main container is skipped, we only add its content to skipped but not the file itself
@@ -174,11 +175,6 @@ def scan(
 
                     continue
 
-                # If main container is scanned, we consider all files to be scanned
-                self._skipped = [
-                    item for item in self._skipped if item.source != skipped.source
-                ]
-
         return self._generate_results()
 
     def _scan_source(

modelscan/scanners/h5/scan.py

@@ -90,7 +90,7 @@ def _scan_keras_h5_file(self, model: Model) -> Optional[ScanResults]:
             )
 
     def _check_model_config(self, model: Model) -> bool:
-        with h5py.File(model.get_stream(), "r") as model_hdf5:
+        with h5py.File(model.get_stream()) as model_hdf5:
             if "model_config" in model_hdf5.attrs.keys():
                 return True
             else:
@@ -100,7 +100,7 @@ def _check_model_config(self, model: Model) -> bool:
     def _get_keras_h5_operator_names(self, model: Model) -> Optional[List[Any]]:
         # Todo: source isn't guaranteed to be a file
 
-        with h5py.File(model.get_stream(), "r") as model_hdf5:
+        with h5py.File(model.get_stream()) as model_hdf5:
             try:
                 if not "model_config" in model_hdf5.attrs.keys():
                     return None

modelscan/scanners/keras/scan.py

@@ -79,22 +79,27 @@ def _scan_keras_config_file(self, model: Model) -> ScanResults:
 
         # if self._check_json_data(source, config_file):
 
-        operators_in_model = self._get_keras_operator_names(model)
-        if operators_in_model:
-            if "JSONDecodeError" in operators_in_model:
-                return ScanResults(
-                    [],
-                    [
-                        ModelScanError(
-                            self.name(),
-                            ErrorCategories.JSON_DECODE,
-                            f"Not a valid JSON data",
-                            str(model.get_source()),
-                        )
-                    ],
-                    [],
-                )
+        try:
+            operators_in_model = self._get_keras_operator_names(model)
+        except json.JSONDecodeError as e:
+            logger.error(
+                f"Not a valid JSON data from source: {model.get_source()}, error: {e}"
+            )
 
+            return ScanResults(
+                [],
+                [
+                    ModelScanError(
+                        self.name(),
+                        ErrorCategories.JSON_DECODE,
+                        f"Not a valid JSON data",
+                        str(model.get_source()),
+                    )
+                ],
+                [],
+            )
+
+        if operators_in_model:
             return KerasLambdaDetectScan._check_for_unsafe_tf_keras_operator(
                 module_name=machine_learning_library_name,
                 raw_operator=operators_in_model,
@@ -112,22 +117,15 @@ def _scan_keras_config_file(self, model: Model) -> ScanResults:
             )
 
     def _get_keras_operator_names(self, model: Model) -> List[str]:
-        try:
-            model_config_data = json.load(model.get_stream())
-
-            lambda_layers = [
-                layer.get("config", {}).get("function", {})
-                for layer in model_config_data.get("config", {}).get("layers", {})
-                if layer.get("class_name", {}) == "Lambda"
-            ]
-            if lambda_layers:
-                return ["Lambda"] * len(lambda_layers)
-
-        except json.JSONDecodeError as e:
-            logger.error(
-                f"Not a valid JSON data from source: {model.get_source()}, error: {e}"
-            )
-            return ["JSONDecodeError"]
+        model_config_data = json.load(model.get_stream())
+
+        lambda_layers = [
+            layer.get("config", {}).get("function", {})
+            for layer in model_config_data.get("config", {}).get("layers", {})
+            if layer.get("class_name", {}) == "Lambda"
+        ]
+        if lambda_layers:
+            return ["Lambda"] * len(lambda_layers)
 
         return []
 

tests/test_modelscan.py

@@ -452,10 +452,7 @@ def test_scan_zip(zip_file_path: Any) -> None:
     ms = ModelScan()
     results = ms.scan(f"{zip_file_path}/test.zip")
     assert results["summary"]["scanned"]["scanned_files"] == [f"test.zip:data.pkl"]
-    assert [
-        skipped_file["source"]
-        for skipped_file in results["summary"]["skipped"]["skipped_files"]
-    ] == ["test.zip"]
+    assert results["summary"]["skipped"]["skipped_files"] == []
     assert ms.issues.all_issues == expected
 
 
@@ -1242,10 +1239,7 @@ def test_scan_directory_path(file_path: str) -> None:
         f"benign0_v3.dill",
         f"benign0_v4.dill",
     }
-    assert [
-        skipped_file["source"]
-        for skipped_file in results["summary"]["skipped"]["skipped_files"]
-    ] == ["malicious1.zip"]
+    assert results["summary"]["skipped"]["skipped_files"] == []
     assert results["errors"] == []
 
 
@@ -1293,7 +1287,19 @@ def test_scan_keras(keras_file_path: Any, file_extension: str) -> None:
             f"safe{file_extension}"
         ]
 
-        assert results["summary"]["skipped"]["skipped_files"] == []
+        if file_extension == ".keras":
+            assert set(
+                [
+                    skipped_file["source"]
+                    for skipped_file in results["summary"]["skipped"]["skipped_files"]
+                ]
+            ) == {
+                f"safe{file_extension}:metadata.json",
+                f"safe{file_extension}:config.json",
+                f"safe{file_extension}:model.weights.h5",
+            }
+        else:
+            assert results["summary"]["skipped"]["skipped_files"] == []
 
         assert results["errors"] == []