PYSEC-2026-3252 TensorFlow vulnerable to `CHECK` fail in `DenseBincount`

Impact DenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf binaryoutput = True input =...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`

ImpactIf FakeQuantWithMinMaxVarsPerChannel is given min or max tensors of a rank other than one, it results in a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfnumbits = 8narrowrange = Falseinputs = tf.constant0, shape=4, dtype=tf.float32min =...

TensorFlow vulnerable to `CHECK` fail in `RaggedTensorToVariant`

ImpactIf RaggedTensorToVariant is given a rtnestedsplits list that contains tensors of ranks other than one, it results in a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfbatchedinput = Truertnestedsplits = tf.constant0,32,64, shape=3,...

TensorFlow vulnerable to `CHECK` fail in `QuantizeAndDequantizeV3`

ImpactIf QuantizeAndDequantizeV3 is given a nonscalar numbits input tensor, it results in a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfsignedinput = Truerangegiven = Falsenarrowrange = Falseaxis = -1input = tf.constant-3.5, shape=1,...

PYSEC-2026-3149 TensorFlow vulnerable to `CHECK` fail in `QuantizeAndDequantizeV3`

Impact If QuantizeAndDequantizeV3 is given a nonscalar numbits input tensor, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf signedinput = True rangegiven = False narrowrange = False axis = -1 input = tf.constant-3.5, shape=1,...

PYSEC-2026-3348 TensorFlow vulnerable to `CHECK` fail in `RaggedTensorToVariant`

Impact If RaggedTensorToVariant is given a rtnestedsplits list that contains tensors of ranks other than one, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf batchedinput = True rtnestedsplits = tf.constant0,32,64, shape=3,...

TensorFlow vulnerable to `CHECK` failure in `AvgPoolOp`

ImpactThe AvgPoolOp function takes an argument ksize that must be positive but is not checked. A negative ksize can trigger a CHECK failure and crash the program.pythonimport tensorflow as tfimport numpy as npvalue = np.ones1, 1, 1, 1ksize = 1, 1e20, 1, 1strides = 1, 1, 1, 1padding =...

TensorFlow vulnerable to `CHECK` failure in `AvgPoolOp`

ImpactThe AvgPoolOp function takes an argument ksize that must be positive but is not checked. A negative ksize can trigger a CHECK failure and crash the program.pythonimport tensorflow as tfimport numpy as npvalue = np.ones1, 1, 1, 1ksize = 1, 1e20, 1, 1strides = 1, 1, 1, 1padding =...

PYSEC-2026-3215 TensorFlow vulnerable to `CHECK` failure in `AvgPoolOp`

Impact The AvgPoolOp function takes an argument ksize that must be positive but is not checked. A negative ksize can trigger a CHECK failure and crash the program. python import tensorflow as tf import numpy as np value = np.ones1, 1, 1, 1 ksize = 1, 1e20, 1, 1 strides = 1, 1, 1, 1 padding = 'SAM...

PYSEC-2026-3306 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`

Impact If FakeQuantWithMinMaxVarsPerChannel is given min or max tensors of a rank other than one, 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=4, dtype=tf.float32 min ...

PT-2026-59822

Impact When MaxPool receives a window size input array ksize with dimensions greater than its input tensor input, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np input = np.ones1, 1, 1, 1 ksize = 1, 1, 2, ...

PT-2026-59847

Impact When the parameter summarize of tf.raw ops.Print is zero, the new method SummarizeArray will reference to a nullptr, leading to a seg fault. python import tensorflow as tf tf.raw ops.Printinput = tf.constant1, 1, 1, 1,dtype=tf.int32, data = False, False, False, False, False, False, False,...

PT-2026-59024

Impact If the 2FA was activated, it was possible during a short moment after the authentication of an user to bypass its authentication. Patches This is fixed in the version 0.112. Users should upgrade to this version as soon as possible...

PT-2026-59863

Impact When TensorListScatter and TensorListScatterV2 receive an element shape of a rank greater than one, they give a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg 0=tf.random.uniformshape=2, 2, 2, dtype=tf.float16, maxval=None arg...

PT-2026-59988

Impact When TensorListScatter and TensorListScatterV2 receive an element shape of a rank greater than one, they give a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg 0=tf.random.uniformshape=2, 2, 2, dtype=tf.float16, maxval=None arg...

PT-2026-59800

Impact If QuantizedInstanceNorm is given x min or x max 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 output range given = False given y min = 0 given y max = 0 variance epsilon = 1e-05 min separation =...

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 =...

PT-2026-59872

Impact The implementation of AvgPool3DGradOp does not fully validate the input orig input shape. 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 paddin...

PT-2026-59994

Impact The implementation of AvgPool3DGradOp does not fully validate the input orig input shape. 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 paddin...

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 =...