45 matches found
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 =...
CVE-2022-35999
TensorFlow is an open source platform for machine learning. When Conv2DBackpropInput receives empty outbackprop inputs e.g. 3, 1, 0, 1, the current CPU/GPU kernels CHECK fail one with dnnl, the other with cudnn. This can be used to trigger a denial of service attack. We have patched the issue in...
CVE-2022-35999 `CHECK` fail in `Conv2DBackpropInput` in TensorFlow
TensorFlow is an open source platform for machine learning. When Conv2DBackpropInput receives empty outbackprop inputs e.g. 3, 1, 0, 1, the current CPU/GPU kernels CHECK fail one with dnnl, the other with cudnn. This can be used to trigger a denial of service attack. We have patched the issue in...
CVE-2022-35999
TensorFlow CVE-2022-35999 affects Conv2DBackpropInput: when out_backprop is empty (example [3,1,0,1]), CPU/GPU kernels fail CHECKs, enabling potential denial of service. A patch was committed (27a65a43cf763897fecfa5cdb5cc653fc5dd0346) and will be included in TensorFlow 2.10.0; the patch will also...
CVE-2022-35999 `CHECK` fail in `Conv2DBackpropInput` in TensorFlow
TensorFlow is an open source platform for machine learning. When Conv2DBackpropInput receives empty outbackprop inputs e.g. 3, 1, 0, 1, the current CPU/GPU kernels CHECK fail one with dnnl, the other with cudnn. This can be used to trigger a denial of service attack. We have patched the issue in...
CVE-2022-35969
TensorFlow is an open source platform for machine learning. 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. We have patched the issue in GitHub commit...
Stack overflow
TensorFlow is an open source platform for machine learning. 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. We have patched the issue in GitHub commit...
CVE-2022-35969 `CHECK` fail in `Conv2DBackpropInput` in TensorFlow
TensorFlow is an open source platform for machine learning. 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. We have patched the issue in GitHub commit...
CVE-2022-35969 `CHECK` fail in `Conv2DBackpropInput` in TensorFlow
TensorFlow is an open source platform for machine learning. 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. We have patched the issue in GitHub commit...
CVE-2022-35969 `CHECK` fail in `Conv2DBackpropInput` in TensorFlow
TensorFlow is an open source platform for machine learning. 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. We have patched the issue in GitHub commit...
CVE-2022-35969
TensorFlow is an open source platform for machine learning. 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. We have patched the issue in GitHub commit...
GHSA-37JF-MJV6-XFQW TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
Impact When Conv2DBackpropInput receives empty outbackprop inputs e.g. 3, 1, 0, 1, the current CPU/GPU kernels CHECK fail one with dnnl, the other with cudnn. This can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np inputsizes = 3, 1, 1, 2 filter =...
TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
Impact When Conv2DBackpropInput receives empty outbackprop inputs e.g. 3, 1, 0, 1, the current CPU/GPU kernels CHECK fail one with dnnl, the other with cudnn. This can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np inputsizes = 3, 1, 1, 2 filter =...
Google TensorFlow 安全漏洞
Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google, Inc. in the United States. Google TensorFlow suffers from a security vulnerability that stems from a failure of the current CPU/GPU kernel assertion one with dnnl and the other with cudnn when...
Google TensorFlow 安全漏洞
Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google. Google TensorFlow has a security vulnerability that stems from the fact that the implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives an assertion failu...
CVE-2022-35969: Reachable Assertion
TensorFlow is an open source platform for machine learning. 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. We have patched the issue in GitHub commit...
CVE-2022-35999: Reachable Assertion
TensorFlow is an open source platform for machine learning. When Conv2DBackpropInput receives empty outbackprop inputs e.g. 3, 1, 0, 1, the current CPU/GPU kernels CHECK fail one with dnnl, the other with cudnn. This can be used to trigger a denial of service attack. We have patched the issue in...
Division by 0 in `Conv2DBackpropInput`
Impact An attacker can trigger a division by 0 in tf.rawops.Conv2DBackpropInput: python import tensorflow as tf inputtensor = tf.constant52, 1, 1, 5, shape=4, dtype=tf.int32 filtertensor = tf.constant, shape=0, 1, 5, 0, dtype=tf.float32 outbackprop = tf.constant, shape=52, 1, 1, 0, dtype=tf.float...
TensorFlow divide-by-zero error vulnerability (CNVD-2021-36565)
Google TensorFlow is an end-to-end open source machine learning platform. A divide-by-zero error vulnerability exists in the tf.rawops.Conv2DBackpropInput implementation in TensorFlow versions prior to 2.5.0. No detailed vulnerability details are provided at this time...