55039 matches found
PT-2026-59806
Impact NPE in RandomShuffle with XLA enable python import tensorflow as tf func = tf.raw ops.RandomShuffle para = 'value': 1e+20, 'seed': -4294967297, 'seed2': -2147483649 @tf.functionjit compile=True def test: y = funcpara return y test Patches We have patched the issue in GitHub commit...
PT-2026-59797
Impact When mlir::tfg::ConvertGenericFunctionToFunctionDef is given empty function attributes, it gives a null dereference. cpp // Import the function attributes with a tf. prefix to match the current // infrastructure expectations. for const auto& namedAttr : func.attr const std::string& name =...
PT-2026-59977
Impact If LowerBound or UpperBound is given an emptysorted inputs 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 out type = tf.int32 sorted inputs = tf.constant, shape=10,0, dtype=tf.float32...
PT-2026-59951
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.raw ops.UnbatchGradoriginal input= tf.constant1,batch index=tf.constant0,0...
PT-2026-59874
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...
PT-2026-59947
Impact If BCast::ToShape is given input larger than an int32, it will crash, despite being supposed to handle up to an int64. An example can be seen in tf.experimental.numpy.outer by passing in large input to the input b. python import tensorflow as tf value = tf.constantshape=2, 1024, 1024, 1024...
PT-2026-59907
Impact TFversion 2.11.0 //tensorflow/core/ops/array ops.cc:1067 const Tensor hypothesis shape t = c-input tensor2; std::vector dimshypothesis shape t-NumElements - 1; for int i = 0; i MakeDimstd::maxh valuesi, t valuesi; if hypothesis shape t is empty, hypothesis shape t-NumElements - 1 will be...
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 =...
PT-2026-59809
Impact If MirrorPadGrad is given outsize input paddings, TensorFlow will give a heap OOB error. python import tensorflow as tf tf.raw ops.MirrorPadGradinput=1, paddings=0x77f00000,0xa000000, mode = 'REFLECT' Patches We have patched the issue in GitHub commit...
PT-2026-59861
Impact If QuantizeDownAndShrinkRange is given nonscalar inputs for input min or input max, 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 input = tf.constant1, shape=3, dtype=tf.qint32 input min = tf.constant,...
PT-2026-59795
Impact The function MakeGrapplerFunctionItem takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. python import tensorflow as tf @tf.function def test: tf.ra...
PT-2026-59801
Impact When tensorflow::full type::SubstituteFromAttrs receives a FullTypeDef& t that is not exactly three args, it triggers a CHECK-fail instead of returning a status. cpp Status SubstituteForEachAttrMap& attrs, FullTypeDef& t DCHECK EQt.args size, 3; const auto& cont = t.args0; const auto& tmpl...
PT-2026-59941
Impact When tensorflow::full type::SubstituteFromAttrs receives a FullTypeDef& t that is not exactly three args, it triggers a CHECK-fail instead of returning a status. cpp Status SubstituteForEachAttrMap& attrs, FullTypeDef& t DCHECK EQt.args size, 3; const auto& cont = t.args0; const auto& tmpl...
PT-2026-59883
Impact When tf.raw ops.ResizeNearestNeighborGrad is given a large size input, it overflows. import tensorflow as tf align corners = True half pixel centers = False grads = tf.constant1, shape=1,8,16,3, dtype=tf.float16 size = tf.constant1879048192,1879048192, shape=2, dtype=tf.int32 tf.raw...
PT-2026-59738
Impact Out of bounds read in GRUBlockCellGrad python func = tf.raw ops.GRUBlockCellGrad para = 'x': 21.1, 156.2, 83.3, 115.4, 'h prev': array136.5, 136.6, 'w ru': array26.7, 0.8, 47.9, 26.1, 26.2, 26.3, 'w c': array 0.4, 31.5, 0.6, 'b ru': array0.1, 0.2 , dtype=float32, 'b c': 0x41414141, 'r':...
PT-2026-59921
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-2026-59753
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-2026-59937
Impact The function MakeGrapplerFunctionItem takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. python import tensorflow as tf @tf.function def test: tf.ra...
PT-2026-59987
Impact If QuantizeDownAndShrinkRange is given nonscalar inputs for input min or input max, 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 input = tf.constant1, shape=3, dtype=tf.qint32 input min = tf.constant,...
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 =...