2349 matches found
imgaug contains an insecure deserialization vulnerability in BackgroundAugmenter class within multicore.py module
The imgaug library thru 0.4.0 contains an insecure deserialization vulnerability in its BackgroundAugmenter class within the multicore.py module. The class uses Python's pickle module to deserialize data received via a multiprocessing queue in the augmentimagesworker method without any safety...
PYSEC-2026-356 imgaug contains an insecure deserialization vulnerability in BackgroundAugmenter class within multicore.py module
The imgaug library thru 0.4.0 contains an insecure deserialization vulnerability in its BackgroundAugmenter class within the multicore.py module. The class uses Python's pickle module to deserialize data received via a multiprocessing queue in the augmentimagesworker method without any safety...
PYSEC-2026-406 mamba language model framework vulnerable to insecure deserialization when loading pre-trained models from HuggingFace Hub
The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization CWE-502 when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.frompretrained method uses torch.load to load the pytorchmodel.bin weight file without enabling the security-restrictive...
PYSEC-2026-282 APScheduler's JSONSerializer and CBORSerializer are vulnerable to Remote Code Execution (RCE) via Insecure Deserialization
The JSONSerializer and CBORSerializer in APScheduler all versions including 3.10.x and 4.0.0a5 are vulnerable to Remote Code Execution RCE via Insecure Deserialization. The unmarshalobject function allows for arbitrary class instantiation and state injection by dynamically importing modules and...
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization CWE-502 through its predict method. When a user provides a dataset file path to the predict method, the framework automatically determines the file format. If the file is a pickle .pkl file, it is loaded using...
Horovod contains an insecure deserialization vulnerability in its KVStore HTTP server component
Horovod thru 0.28.1 contains an insecure deserialization vulnerability CWE-502 in its KVStore HTTP server component. The KVStore server, used for distributed task coordination, lacks authentication and authorization controls, allowing any remote attacker to write arbitrary data via HTTP PUT...
PYSEC-2026-354 Horovod contains an insecure deserialization vulnerability in its KVStore HTTP server component
Horovod thru 0.28.1 contains an insecure deserialization vulnerability CWE-502 in its KVStore HTTP server component. The KVStore server, used for distributed task coordination, lacks authentication and authorization controls, allowing any remote attacker to write arbitrary data via HTTP PUT...
APScheduler's JSONSerializer and CBORSerializer are vulnerable to Remote Code Execution (RCE) via Insecure Deserialization
The JSONSerializer and CBORSerializer in APScheduler all versions including 3.10.x and 4.0.0a5 are vulnerable to Remote Code Execution RCE via Insecure Deserialization. The unmarshalobject function allows for arbitrary class instantiation and state injection by dynamically importing modules and...
PYSEC-2026-404 Ludwig framework is vulnerable to insecure deserialization through its predict() method.
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization CWE-502 through its predict method. When a user provides a dataset file path to the predict method, the framework automatically determines the file format. If the file is a pickle .pkl file, it is loaded using...
mamba language model framework vulnerable to insecure deserialization when loading pre-trained models from HuggingFace Hub
The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization CWE-502 when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.frompretrained method uses torch.load to load the pytorchmodel.bin weight file without enabling the security-restrictive...
Ludwig framework is vulnerable to insecure deserialization in its model serving component
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization CWE-502 in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load without enabling the security-restrictive weightsonly=True...
PYSEC-2026-405 Ludwig framework is vulnerable to insecure deserialization in its model serving component
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization CWE-502 in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load without enabling the security-restrictive weightsonly=True...
BentoML Allows Remote Code Execution (RCE) via Insecure Deserialization
SummaryA Remote Code Execution RCE vulnerability caused by insecure deserialization has been identified in the latest versionv1.4.2 of BentoML. It allows any unauthenticated user to execute arbitrary code on the server. DetailsIt exists an unsafe code segment in serde.py: Pythondef...
PYSEC-2026-294 BentoML Allows Remote Code Execution (RCE) via Insecure Deserialization
Summary A Remote Code Execution RCE vulnerability caused by insecure deserialization has been identified in the latest versionv1.4.2 of BentoML. It allows any unauthenticated user to execute arbitrary code on the server. Details It exists an unsafe code segment in serde.py: Python def...
PT-2026-53489
The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization CWE-502 when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from pretrained method uses torch.load to load the pytorch model.bin weight file without enabling the security-restrictive...
PT-2026-53488
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization CWE-502 in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load without enabling the security-restrictive weights only=True...
PT-2026-53445
The imgaug library thru 0.4.0 contains an insecure deserialization vulnerability in its BackgroundAugmenter class within the multicore.py module. The class uses Python's pickle module to deserialize data received via a multiprocessing queue in the augment images worker method without any safety...
PT-2026-53379
The JSONSerializer and CBORSerializer in APScheduler all versions including 3.10.x and 4.0.0a5 are vulnerable to Remote Code Execution RCE via Insecure Deserialization. The unmarshal object function allows for arbitrary class instantiation and state injection by dynamically importing modules and...
PT-2026-53487
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization CWE-502 through its predict method. When a user provides a dataset file path to the predict method, the framework automatically determines the file format. If the file is a pickle .pkl file, it is loaded using pandas.read...
PT-2026-53389
Summary A Remote Code Execution RCE vulnerability caused by insecure deserialization has been identified in the latest versionv1.4.2 of BentoML. It allows any unauthenticated user to execute arbitrary code on the server. Details It exists an unsafe code segment in serde.py: Python def deserialize...