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Security fix: Update MD5 usage with usedforsecurity=False #799

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Security fix: Update MD5 usage with usedforsecurity=False #799

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c92a7f0
security: add usedforsecurity=False to hashlib.md5 in prepare_voxcele…
Ismail-Benali Aug 29, 2026
8727d98
security: replace unsafe pickle.load with SafeUnpickler in TF checkpo…
Ismail-Benali Aug 29, 2026
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2 changes: 1 addition & 1 deletion TTS/speaker_encoder/utils/prepare_voxceleb.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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)

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11 changes: 10 additions & 1 deletion TTS/tts/tf/utils/generic_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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:
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11 changes: 10 additions & 1 deletion TTS/tts/tf/utils/io.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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:
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11 changes: 10 additions & 1 deletion TTS/vocoder/tf/utils/io.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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:
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