Allocation of Resources Without Limits or Throttling in the HDF5 weight loading component in Google Keras 3.0.0 through 3.13.0 on all platforms allows a remote attacker to cause a Denial of Service (D
Arbitrary file read in the model loading mechanism (HDF5 integration) in Keras versions 3.0.0 through 3.13.1 on all supported platforms allows a remote attacker to read local files and disclose sensit
The Keras Model.load_model method can be exploited to achieve arbitrary code execution, even with safe_mode=True.
One can create a specially crafted .h5/.hdf5 model archive that, when loaded via Mode
The Keras.Model.load_model method, including when executed with the intended security mitigation safe_mode=True, is vulnerable to arbitrary local file loading and Server-Side Request Forgery (SSRF).
The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains an insecure deserialization vulnerability (CWE-502) in its Kubeflow component's model loading functionality. When loading model weights fr
A vulnerability, which was classified as problematic, has been found in HDF5 1.14.6. This issue affects the function H5C__load_entry of the file /src/H5Centry.c. The manipulation leads to resource con
A vulnerability was found in HDF5 up to 1.14.6. It has been rated as critical. Affected by this issue is the function H5FL__blk_gc_list of the file src/H5FL.c. The manipulation of the argument H5FL_bl
An issue was discovered TensorFlow v2.18.0. A Denial of Service (DoS) occurs when padding is set to 'valid' in tf.keras.layers.Conv2D.
A vulnerability in the `TFSMLayer` class of the `keras` package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of `.keras` models, even when `sa
The Keras Model.load_model function permits arbitrary code execution, even with safe_mode=True, through a manually constructed, malicious .keras archive. By altering the config.json file within the ar
A high-severity remote code execution vulnerability exists in feast-dev/feast version 0.53.0, specifically in the Kubernetes materializer job located at `feast/sdk/python/feast/infra/compute_engines/k
The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability (CWE-502) in the MultitaskClassifier.load() method of the MultitaskClassifier class. The method loads model weight f
The Keras Model.load_model method can be exploited to achieve arbitrary code execution, even with safe_mode=True.
One can create a specially crafted .keras model archive that, when loaded via Model.l
A vulnerability, which was classified as problematic, was found in HDF5 up to 1.14.6. This affects the function H5HL__fl_deserialize of the file src/H5HLcache.c. The manipulation of the argument free_
A heap overflow in the MatroskaFile::createRTPSinkForTrackNumber() function of Live555 Streaming Media v2018.09.02 allows attackers to cause a Denial of Service (DoS) via supplying a crafted MKV file.
HDF5 is software for managing data. Prior to version 1.14.4-2, an attacker who can control an `h5` file parsed by HDF5 can trigger a write-based heap buffer overflow condition. This can lead to a deni
The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability (CWE-502) in the Trainer.load() method of the Trainer class. The method loads model checkpoint files using torch.loa
HDF5 is software for managing data. In 1.14.1-2 and earlier, an attacker who can control an h5 file parsed by HDF5 can trigger a write-based heap buffer overflow condition in the H5T__ref_mem_setnull
A vulnerability, which was classified as problematic, has been found in HDF5 up to 1.14.6. Affected by this issue is the function H5F_addr_encode_len of the file src/H5Fint.c. The manipulation of the
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 us
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