PYSEC-2026-948 TensorFlow vulnerable to segfault in `QuantizedBiasAdd`

Impact If QuantizedBiasAdd is given mininput, maxinput, minbias, maxbias 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 outtype = tf.qint32 input = tf.constant85,170,255, shape=3, dtype=tf.quint8 bias =...

PYSEC-2026-959 TensorFlow vulnerable to segfault in `QuantizedMatMul`

Impact If QuantizedMatMul is given nonscalar input for: - mina - maxa - minb - maxb It gives a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 transposea = False transposeb = False Tactivation = tf.quint8 a = tf.constant7,...

PYSEC-2026-995 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-2026-1028 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 =...

PYSEC-2026-947 TensorFlow vulnerable to segfault in `SparseBincount`

Impact If SparseBincount is given inputs for indices, values, and denseshape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf binaryoutput = True indices = tf.random.uniformshape=, minval=-10000...

PYSEC-2026-940 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"...

PYSEC-2026-1037 TensorFlow vulnerable to segfault in `QuantizedAdd`

Impact If 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. python import tensorflow as tf Toutput = tf.qint32 x = tf.constant140, shape=1, dtype=tf.quint8 y = tf.constant26, shape=10,...

PYSEC-2026-980 TensorFlow vulnerable to `CHECK` fail in `tf.linalg.matrix_rank`

Impact When tf.linalg.matrixrank receives an empty input a, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf a = tf.constant, shape=0, 1, 1, dtype=tf.float32 tf.linalg.matrixranka=a Patches We have patched the issue in GitHub...

PYSEC-2026-975 TensorFlow vulnerable to `CHECK` fail in `LRNGrad`

Impact If LRNGrad is given an outputimage input tensor that is not 4-D, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf depthradius = 1 bias = 1.59018219 alpha = 0.117728651 beta = 0.404427052 inputgrads = tf.random.uniformshape=4,...

PYSEC-2026-977 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-2026-979 TensorFlow vulnerable to `CHECK` fail in `TensorListFromTensor`

Impact When TensorListFromTensor receives an elementshape of a rank greater than one, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=6, 6, 2, dtype=tf.bfloat16, maxval=None arg1=tf.random.uniformshape=6, 9, 1, 3,...

PYSEC-2026-1047 TensorFlow vulnerable to Int overflow in `RaggedRangeOp`

Impact The RaggedRangOp function takes an argument limits that is eventually used to construct a TensorShape as an int64. If limits is a very large float, it can overflow when converted to an int64. This triggers an InvalidArgument but also throws an abort signal that crashes the program. python...

PYSEC-2026-1044 TensorFlow vulnerable to `CHECK` fail in `SetSize`

Impact When SetSize receives an input setshape that is not a 1D tensor, it gives a CHECK fails that can be used to trigger a denial of service attack. python import tensorflow as tf arg0=1 arg1=1,1 arg2=1 arg3=True arg4='' tf.rawops.SetSizesetindices=arg0, setvalues=arg1, setshape=arg2,...

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...

PYSEC-2026-1005 TensorFlow vulnerable to `CHECK` failures in `UnbatchGradOp`

Impact The UnbatchGradOp function takes an argument id that is assumed to be a scalar. A nonscalar id can trigger a CHECK failure and crash the program. python import numpy as np import tensorflow as tf id is not scalar tf.rawops.UnbatchGradoriginalinput= tf.constant1,batchindex=tf.constant0,0,0 ...

PYSEC-2026-1030 TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`

Impact If LowerBound or UpperBound is given an emptysortedinputs input, it results in a nullptr dereference, leading to a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outtype = tf.int32 sortedinputs = tf.constant, shape=10,0, dtype=tf.float32...

PYSEC-2026-1036 TensorFlow vulnerable to `CHECK` failure in `TensorListReserve` via missing validation

Impact In core/kernels/listkernels.cc's TensorListReserve, numelements is assumed to be a tensor of size 1. When a numelements of more than 1 element is provided, then tf.rawops.TensorListReserve fails the CHECKEQ in CheckIsAlignedAndSingleElement. python import tensorflow as tf...

PYSEC-2026-988 TensorFlow vulnerable to segfault in `BlockLSTMGradV2`

Impact The implementation of BlockLSTMGradV2 does not fully validate its inputs. - wci, wcf, wco, b must be rank 1 - w, csprev, hprev must be rank 2 - x must be rank 3 This results in a a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf usepeephole =...

PYSEC-2026-1046 TensorFlow vulnerable to `CHECK` failures in `AvgPool3DGrad`

Impact The implementation of AvgPool3DGradOp does not fully validate the input originputshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 1, 1, 1, 1 strides = 1, 1, 1, 1, 1 padding ...

PYSEC-2026-1006 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...