diff --git a/TTS/speaker_encoder/utils/prepare_voxceleb.py b/TTS/speaker_encoder/utils/prepare_voxceleb.py
index 758e1cb3b..2c7208b53 100644
--- a/TTS/speaker_encoder/utils/prepare_voxceleb.py
+++ b/TTS/speaker_encoder/utils/prepare_voxceleb.py
@@ -100,7 +100,7 @@ def download_and_extract(directory, subset, urls):
         extract_path = zip_filepath.strip(".zip")
 
         # check zip file md5sum
-        md5 = hashlib.md5(open(zip_filepath, 'rb').read()).hexdigest()
+        md5 = hashlib.md5(open(zip_filepath, 'rb').read(), usedforsecurity=False).hexdigest()
         if md5 != MD5SUM[subset]:
             raise ValueError("md5sum of %s mismatch" % zip_filepath)
 
diff --git a/TTS/tts/tf/utils/generic_utils.py b/TTS/tts/tf/utils/generic_utils.py
index 7eba946b1..105e00816 100644
--- a/TTS/tts/tf/utils/generic_utils.py
+++ b/TTS/tts/tf/utils/generic_utils.py
@@ -18,8 +18,17 @@ def save_checkpoint(model, optimizer, current_step, epoch, r, output_path, **kwa
     pickle.dump(state, open(output_path, 'wb'))
 
 
+class SafeUnpickler(pickle.Unpickler):
+    def find_class(self, module, name):
+        if module == "builtins" and name in {"dict", "list", "tuple", "set", "int", "float", "str", "bytes", "bool"}:
+            return super().find_class(module, name)
+        if "numpy" in module:
+            return super().find_class(module, name)
+        raise pickle.UnpicklingError(f"Unsafe global {module}.{name}")
+
+
 def load_checkpoint(model, checkpoint_path):
-    checkpoint = pickle.load(open(checkpoint_path, 'rb'))
+    checkpoint = SafeUnpickler(open(checkpoint_path, 'rb')).load()
     chkp_var_dict = {var.name: var.numpy() for var in checkpoint['model']}
     tf_vars = model.weights
     for tf_var in tf_vars:
diff --git a/TTS/tts/tf/utils/io.py b/TTS/tts/tf/utils/io.py
index 143422d27..a6879b3b6 100644
--- a/TTS/tts/tf/utils/io.py
+++ b/TTS/tts/tf/utils/io.py
@@ -16,8 +16,17 @@ def save_checkpoint(model, optimizer, current_step, epoch, r, output_path, **kwa
     pickle.dump(state, open(output_path, 'wb'))
 
 
+class SafeUnpickler(pickle.Unpickler):
+    def find_class(self, module, name):
+        if module == "builtins" and name in {"dict", "list", "tuple", "set", "int", "float", "str", "bytes", "bool"}:
+            return super().find_class(module, name)
+        if "numpy" in module:
+            return super().find_class(module, name)
+        raise pickle.UnpicklingError(f"Unsafe global {module}.{name}")
+
+
 def load_checkpoint(model, checkpoint_path):
-    checkpoint = pickle.load(open(checkpoint_path, 'rb'))
+    checkpoint = SafeUnpickler(open(checkpoint_path, 'rb')).load()
     chkp_var_dict = {var.name: var.numpy() for var in checkpoint['model']}
     tf_vars = model.weights
     for tf_var in tf_vars:
diff --git a/TTS/vocoder/tf/utils/io.py b/TTS/vocoder/tf/utils/io.py
index c73c9cd86..81423c5ae 100644
--- a/TTS/vocoder/tf/utils/io.py
+++ b/TTS/vocoder/tf/utils/io.py
@@ -15,9 +15,18 @@ def save_checkpoint(model, current_step, epoch, output_path, **kwargs):
     pickle.dump(state, open(output_path, 'wb'))
 
 
+class SafeUnpickler(pickle.Unpickler):
+    def find_class(self, module, name):
+        if module == "builtins" and name in {"dict", "list", "tuple", "set", "int", "float", "str", "bytes", "bool"}:
+            return super().find_class(module, name)
+        if "numpy" in module:
+            return super().find_class(module, name)
+        raise pickle.UnpicklingError(f"Unsafe global {module}.{name}")
+
+
 def load_checkpoint(model, checkpoint_path):
     """ Load TF Vocoder model """
-    checkpoint = pickle.load(open(checkpoint_path, 'rb'))
+    checkpoint = SafeUnpickler(open(checkpoint_path, 'rb')).load()
     chkp_var_dict = {var.name: var.numpy() for var in checkpoint['model']}
     tf_vars = model.weights
     for tf_var in tf_vars: