1583 matches found
PT-2026-59969
Impact ParameterizedTruncatedNormal assumes shape is of type int32. A valid shape of type int64 results in a mismatched type CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf seed = 1618 seed2 = 0 shape = tf.random.uniformshape=3, minval=-10000,...
PT-2026-59952
Impact When tf.quantization.fake quant with min max vars per channel gradient 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 arg 0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None arg...
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-2026-59702
Impact The implementation of AvgPoolGrad does not fully validate the input orig input shape. 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" data format = "NHWC" orig...
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-2026-59911
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-2026-59877
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-2026-59941
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-2026-59942
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-2026-59789
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...
PT-2026-59799
Impact A malicious invalid input crashes a tensorflow model Check Failed and can be used to trigger a denial of service attack. To minimize the bug, we built a simple single-layer TensorFlow model containing a Convolution3DTranspose layer, which works well with expected inputs and can be deployed...
PT-2026-59802
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-2026-59795
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-2026-59937
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-2026-59998
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-2026-59753
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-2026-59839
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-2026-59934
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...
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-2026-59705
Impact Inputs dense features or example state data not of rank 2 will trigger a CHECK fail in SdcaOptimizer. python import tensorflow as tf tf.raw ops.SdcaOptimizer sparse example indices=4 tf.random.uniform5,5,5,3, dtype=tf.dtypes.int64, maxval=100, sparse feature indices=4...