45 matches found
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 =...
PT-2026-59974
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 strides = 1, 1, 1, 1 padding = "SAME" use cudnn on gpu = True explicit paddings =...
PT-2026-59844
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 strides = 1, 1, 1, 1 padding = "SAME" use cudnn on gpu = True explicit paddings =...
PYSEC-2026-3269 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`
ImpactWhen 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.pythonimport tensorflow as tfimport numpy as npinputsizes = 3, 1, 1, 2filter =...
TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
ImpactWhen 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.pythonimport tensorflow as tfimport numpy as npinputsizes = 3, 1, 1, 2filter =...
PYSEC-2026-3092 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 =...
PYSEC-2026-1028 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 `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-2026-946 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`
ImpactWhen 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.pythonimport tensorflow as tfimport numpy as npinputsizes = 3, 1, 1, 2filter =...
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...
EUVD-2021-0266
Malware in sbrugna...
EUVD-2022-6674
Malicious code in bioql PyPI...
EUVD-2022-6904
Malicious code in bioql PyPI...
BIT-TENSORFLOW-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...
BIT-TENSORFLOW-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...
SUSE CVE-2021-29525
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in tf.rawops.Conv2DBackpropInput. This is because the...
SUSE 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...
Denial Of Service (DoS)
tensorflow is vulnerable to denial of service. The vulnerability exists in the multiple functions in convgradinputops.cc due to check fail in Conv2DBackpropInput which allows an attacker to cause an application crash by providing malicious input...