PT-2026-59984

Impact In core/kernels/list kernels.cc's TensorListReserve, num elements is assumed to be a tensor of size 1. When a num elements of more than 1 element is provided, then tf.raw ops.TensorListReserve fails the CHECK EQ in CheckIsAlignedAndSingleElement. python import tensorflow as tf tf.raw...

PT-2026-59767

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 num bits = 8 narrow range = False inputs = tf.constant0, shape=2,3, dtype=tf.float32 min = tf.constant...

PT-2026-59986

Impact If QuantizedRelu or QuantizedRelu6 are given nonscalar inputs for min features or max features, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf out type = tf.quint8 features = tf.constant28, shape=4,2, dtype=tf.quint8 min...

PT-2026-59769

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 num bits = 8 narrow range = False inputs = tf.constant0, shape=4, dtype=tf.float32 mi...

PT-2026-59773

Impact When tf.linalg.matrix rank 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.matrix ranka=a Patches We have patched the issue in GitH...

PT-2026-59867

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 binary output = True input =...

PT-2026-59885

Impact If SparseBincount is given inputs for indices, values, and dense shape 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 binary output = True indices = tf.random.uniformshape=,...

PT-2026-59917

Impact If LRNGrad is given an output image 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 depth radius = 1 bias = 1.59018219 alpha = 0.117728651 beta = 0.404427052 input grads =...

PT-2026-59922

Impact When tf.linalg.matrix rank 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.matrix ranka=a Patches We have patched the issue in GitH...

PT-2026-59963

Impact If Save or SaveSlices is run over tensors of an unsupported dtype, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf filename = tf.constant"" tensor names = tf.constant"" Save data = tf.casttf.random.uniformshape=1,...

PT-2026-59712

Impact If SparseBincount is given inputs for indices, values, and dense shape 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 binary output = True indices = tf.random.uniformshape=,...

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-2026-59865

Impact FractionalMaxPoolGrad validates its inputs with CHECK failures instead of with returning errors. If it gets incorrectly sized inputs, the CHECK failure can be used to trigger a denial of service attack: python import tensorflow as tf overlapping = True orig input = tf.constant.453409232,...

PT-2026-59827

Impact When mlir::tfg::ConvertGenericFunctionToFunctionDef is given empty function attributes, it crashes. cpp // We pre-allocate the array of operands and populate it using the // output name to position and control output to position populated // previously. SmallVector ret valsfunc.ret size +...

PT-2026-59845

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...

PT-2026-59981

Impact When RangeSize receives values that do not fit into an int64 t, it crashes. cpp auto size = std::is integral::value ? Eigen::numext::abslimit - start + Eigen::numext::absdelta - T1 / Eigen::numext::absdelta : Eigen::numext::ceil Eigen::numext::abslimit - start / delta; // This check does n...

PT-2026-59772

Impact When TensorListFromTensor receives an element shape of a rank greater than one, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg 0=tf.random.uniformshape=6, 6, 2, dtype=tf.bfloat16, maxval=None arg 1=tf.random.uniformshape=6, 9, 1, 3,...

PT-2026-59850

Impact When tf.quantization.fake quant with min max vars gradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg 0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2,...

PT-2026-59745

Impact When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process. python import tensorflow as tf class QuantConv2DTransposedtf.keras.layers.Layer: def buildself, input shape: self.kernel = self.add weight"kernel", 3, 3,...

PT-2026-59789

Impact When CollectiveGather receives an scalar input input, it gives a CHECK fails that can be used to trigger a denial of service attack. python import tensorflow as tf arg 0=1 arg 1=1 arg 2=1 arg 3=1 arg 4=3, 3,3 arg 5='auto' arg 6=0 arg 7='' tf.raw ops.CollectiveGatherinput=arg 0, group...