PYSEC-2026-3150 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`

Impact If FakeQuantWithMinMaxVars is given min or max tensors of a nonzero rank, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf numbits = 8 narrowrange = False inputs = tf.constant0, shape=2,3, dtype=tf.float32 min = tf.constant0,...

PYSEC-2026-3326 TensorFlow vulnerable to segfault in `QuantizedInstanceNorm`

Impact If QuantizedInstanceNorm is given xmin or xmax tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outputrangegiven = False givenymin = 0 givenymax = 0 varianceepsilon = 1e-05 minseparation = 0.001 x =...

PYSEC-2026-3183 TensorFlow vulnerable to segfault in `QuantizedInstanceNorm`

Impact If QuantizedInstanceNorm is given xmin or xmax tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outputrangegiven = False givenymin = 0 givenymax = 0 varianceepsilon = 1e-05 minseparation = 0.001 x =...

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 =...

PYSEC-2026-3199 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

Impact When tf.quantization.fakequantwithminmaxvarsperchannelgradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None...

PYSEC-2026-3273 TensorFlow vulnerable to segfault in `QuantizedAvgPool`

Impact If QuantizedAvgPool is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "SAME" input = tf.constant1, shape=1,4,4,2,...

PYSEC-2026-3103 TensorFlow vulnerable to segfault in `QuantizedAvgPool`

Impact If QuantizedAvgPool is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "SAME" input = tf.constant1, shape=1,4,4,2,...

PYSEC-2026-3263 TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "VALID" dataformat = "NHWC"...

TensorFlow vulnerable to segfault in `QuantizedAdd`

ImpactIf QuantizedAdd is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfToutput = tf.qint32x = tf.constant140, shape=1, dtype=tf.quint8y = tf.constant26, shape=10, dtype=tf.quint8mi...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

ImpactWhen tf.quantization.fakequantwithminmaxvarsperchannelgradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfarg0=tf.random.uniformshape=1,1, dtype=tf.float32,...

TensorFlow vulnerable to segfault in `QuantizedAvgPool`

ImpactIf QuantizedAvgPool is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfksize = 1, 2, 2, 1strides = 1, 2, 2, 1padding = "SAME"input = tf.constant1, shape=1,4,4,2,...

TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

ImpactThe implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfksize = 1, 2, 2, 1strides = 1, 2, 2, 1padding = "VALID"dataformat = "NHWC"originputshape =...

TensorFlow vulnerable to segfault in `QuantizedAdd`

ImpactIf QuantizedAdd is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfToutput = tf.qint32x = tf.constant140, shape=1, dtype=tf.quint8y = tf.constant26, shape=10, dtype=tf.quint8mi...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

ImpactWhen tf.quantization.fakequantwithminmaxvarsperchannelgradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfarg0=tf.random.uniformshape=1,1, dtype=tf.float32,...

TensorFlow vulnerable to segfault in `QuantizedAvgPool`

ImpactIf QuantizedAvgPool is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfksize = 1, 2, 2, 1strides = 1, 2, 2, 1padding = "SAME"input = tf.constant1, shape=1,4,4,2,...

TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

ImpactThe implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfksize = 1, 2, 2, 1strides = 1, 2, 2, 1padding = "VALID"dataformat = "NHWC"originputshape =...

TensorFlow vulnerable to `CHECK` fail in `TensorListScatter` and `TensorListScatterV2`

ImpactWhen TensorListScatter and TensorListScatterV2 receive an elementshape of a rank greater than one, they give a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfarg0=tf.random.uniformshape=2, 2, 2, dtype=tf.float16, maxval=Nonearg1=tf.random.uniformshape=2,...

PYSEC-2026-3374 TensorFlow vulnerable to `CHECK` fail in `TensorListScatter` and `TensorListScatterV2`

Impact When TensorListScatter and TensorListScatterV2 receive an elementshape of a rank greater than one, they give a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=2, 2, 2, dtype=tf.float16, maxval=None...

PYSEC-2026-3338 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

Impact When tf.quantization.fakequantwithminmaxvarsperchannelgradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None...

PYSEC-2026-3083 TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "VALID" dataformat = "NHWC"...