TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`

ImpactThe implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfstrides = 1, 1, 1, 1padding = "SAME"usecudnnongpu = Trueexplicitpaddings = dataformat =...

PYSEC-2026-3227 TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`

Impact The implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf strides = 1, 1, 1, 1 padding = "SAME" usecudnnongpu = True explicitpaddings =...

PYSEC-2026-3360 TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`

Impact The implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf strides = 1, 1, 1, 1 padding = "SAME" usecudnnongpu = True explicitpaddings =...

TensorFlow vulnerable to floating point exception in `Conv2D`

ImpactIf Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as npwith tf.device"CPU": also can be...

PYSEC-2026-3361 TensorFlow vulnerable to floating point exception in `Conv2D`

Impact If Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np with tf.device"CPU": also can...

PT-2026-59743

Impact When tf.raw ops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows. python import tensorflow as tf mode = "REFLECT" strides = 1, 1, 1, 1 padding = "SAME" resize align corners = False input = tf.constant147, shape=3,3,1,1, dtype=tf.float16 size =...

PT-2026-59975

Impact If Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np with tf.device"CPU": also can...

PT-2026-59904

Impact When tf.raw ops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows. python import tensorflow as tf mode = "REFLECT" strides = 1, 1, 1, 1 padding = "SAME" resize align corners = False input = tf.constant147, shape=3,3,1,1, dtype=tf.float16 size =...

PT-2026-59845

Impact If Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np with tf.device"CPU": also can...

PYSEC-2026-964 Overflow in `FusedResizeAndPadConv2D`

Impact When tf.rawops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows. python import tensorflow as tf mode = "REFLECT" strides = 1, 1, 1, 1 padding = "SAME" resizealigncorners = False input = tf.constant147, shape=3,3,1,1, dtype=tf.float16 size =...

Overflow in `FusedResizeAndPadConv2D`

ImpactWhen tf.rawops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows.pythonimport tensorflow as tfmode = "REFLECT"strides = 1, 1, 1, 1padding = "SAME"resizealigncorners = Falseinput = tf.constant147, shape=3,3,1,1, dtype=tf.float16size = tf.constant1879048192,1879048192,...

TensorFlow vulnerable to floating point exception in `Conv2D`

ImpactIf Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as npwith tf.device"CPU": also can be...

PYSEC-2026-1029 TensorFlow vulnerable to floating point exception in `Conv2D`

Impact If Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np with tf.device"CPU": also can...

CVE-2022-35996

TensorFlow is an open source platform for machine learning. If Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue ...

Vulnerabilities of methods like torch.nn.Conv2d(), torch.nn.functional.hardshrink(), torch.Tensor.view(), and torch.Tensor.mv() in the PyTorch machine learning framework, which allow attackers to trigger a denial-of-service attack.

The vulnerabilities of the methods torch.nn.Conv2d, torch.nn.functional.hardshrink, torch.Tensor.view, and torch.Tensor.mv in the PyTorch machine learning framework are related to uncontrolled resource consumption. Exploiting these vulnerabilities could allow a malicious actor to cause service...

The vulnerability of the `tf.keras.layers.Conv2D()` function in the TensorFlow machine learning system, which allows attackers to trigger a service denial-of-service attack.

The vulnerability of the tf.keras.layers.Conv2D function in TensorFlow’s machine learning system is related to uncontrolled resource consumption when the padding='valid' parameter is used. Exploiting this vulnerability could allow a malicious actor to cause a service failure...

EUVD-2021-0267

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EUVD-2025-31122

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SUSE CVE-2025-55559

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...

Linux Distros Unpatched Vulnerability : CVE-2025-55558

The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - A buffer overflow occurs in pytorch v2.7.0 when a PyTorch model consists of torch.nn.Conv2d, torch.nn.functional.hardshrink, and torch.Tensor.view-torch.mv and ...