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-2026-59912

Impact When the BaseCandidateSamplerOp function receives a value in true classes larger than range max, a heap oob vuln occurs. python tf.raw ops.ThreadUnsafeUnigramCandidateSampler true classes=0x100000,1, num true = 2, num sampled = 2, unique = False, range max = 2, seed = 2, seed2 = 2 Patches ...

PT-2026-59839

Impact When printing a tensor, we get it's data as a const char array since that's the underlying storage and then we typecast it to the element type. However, conversions from char to bool are undefined if the char is not 0 or 1, so sanitizers/fuzzers will crash. Patches We have patched the issu...

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-2026-59773

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-2026-59852

Impact If the stride and window size are not positive for tf.raw ops.AvgPoolGrad, it can give an FPE. python import tensorflow as tf import numpy as np @tf.functionjit compile=True def test: y = tf.raw ops.AvgPoolGradorig input shape=1,0,0,0, grad=0.39117979, ksize=1,0,0,0, strides=1,0,0,0,...

PT-2026-59886

Impact NPE in QuantizedMatMulWithBiasAndDequantize with MKL enable python import tensorflow as tf func = tf.raw ops.QuantizedMatMulWithBiasAndDequantize para='a': tf.constant138, dtype=tf.quint8, 'b': tf.constant4, dtype=tf.qint8, 'bias': 31.81644630432129, 47.21876525878906, 109.95201110839844,...

PT-2026-59998

Impact If a list of quantized tensors is assigned to an attribute, the pywrap code fails to parse the tensor and returns a nullptr, which is not caught. An example can be seen in tf.compat.v1.extract volume patches by passing in quantized tensors as input ksizes. python import numpy as np import...

PT-2026-59942

Impact An input sparse matrix that is not a matrix with a shape with rank 0 will trigger a CHECK fail in tf.raw ops.SparseMatrixNNZ. python import tensorflow as tf tf.raw ops.SparseMatrixNNZsparse matrix= Patches We have patched the issue in GitHub commit f856d02e5322821aad155dad9b3acab1e9f5d693...

PT-2026-59904

Impact When tf.raw ops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows. python import tensorflow as tf mode = "REFLECT" strides = 1, 1, 1, 1 padding = "SAME" resize align corners = False input = tf.constant147, shape=3,3,1,1, dtype=tf.float16 size =...

PT-2026-59911

Impact tf.keras.losses.poisson receives a y pred and y true that are passed through functor::mul in BinaryOp. If the resulting dimensions overflow an int32, TensorFlow will crash due to a size mismatch during broadcast assignment. python import numpy as np import tensorflow as tf true value =...

PT-2026-59894

Impact Constructing a tflite model with a paramater filter input channel of less than 1 gives a FPE. Patches We have patched the issue in GitHub commit 34f8368c535253f5c9cb3a303297743b62442aaa. The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1...

PT-2026-59899

Impact If tf.raw ops.TensorListResize is given a nonscalar value for input size, it results CHECK fail which can be used to trigger a denial of service attack. python import numpy as np import tensorflow as tf a = data structures.tf tensor list newelements = tf.constantvalue=3, 4, 5 b = np.zeros0...

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-2026-59712

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-2026-59867

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-2026-59963

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-2026-59772

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,...