PT-2026-59925

Impact When RandomPoissonV2 receives large input shape and rates, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg 0=tf.random.uniformshape=4,, dtype=tf.int32, maxval=65536 arg 1=tf.random.uniformshape=4, 4, 4, 4, 4, dtype=tf.float32, maxval=No...

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-2026-59976

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-2026-59782

Impact If FractionMaxPoolGrad is given outsize inputs row pooling sequence and col pooling sequence, TensorFlow will crash. python import tensorflow as tf tf.raw ops.FractionMaxPoolGrad orig input = 1, 1, 1, 1, 1, orig output = 1, 1, 1, out backprop = 3, 3, 6, row pooling sequence = -0x4000000, 1...

PT-2026-59733

Impact FPE in TensorListSplit with XLA python import tensorflow as tf func = tf.raw ops.TensorListSplit para = 'tensor': 1, 'element shape': -1, 'lengths': 0 @tf.functionjit compile=True def fuzz jit: y = funcpara return y printfuzz jit Patches We have patched the issue in GitHub commit...

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-2026-59991

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-2026-59917

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-2026-59900

Impact If QuantizedMatMul is given nonscalar input for: - min a - max a - min b - max b It gives a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 transpose a = False transpose b = False Tactivation = tf.quint8 a = tf.constant7,...

PT-2026-59737

Impact If QuantizedMatMul is given nonscalar input for: - min a - max a - min b - max b It gives a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 transpose a = False transpose b = False Tactivation = tf.quint8 a = tf.constant7,...

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-2026-59163

Predictable bucket naming in Vertex AI Experiments in Google Cloud Vertex AI from version 1.21.0 up to but not including 1.133.0 on Google Cloud Platform allows an unauthenticated remote attacker to achieve cross-tenant remote code execution, model theft, and poisoning via pre-creating predictabl...

PT-2026-59928

Impact nn ops.fractional avg pool v2 and nn ops.fractional max pool v2 require the first and fourth elements of their parameter pooling ratio to be equal to 1.0, as pooling on batch and channel dimensions is not supported. python import tensorflow as tf import os import numpy as np from...

PT-2026-59878

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-2026-59894

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-2026-59644

Impact An attacker who uses this vulnerability can craft a PDF which leads to an infinite loop. This requires merging a file with outlines into a writer. Patches This has been fixed in pypdf==6.13.0. Workarounds If you cannot upgrade yet, consider applying the changes from PR 3830...

PT-2026-59722

Impact If QuantizedAvgPool is given min input or max input 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 ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "SAME" input = tf.constant1, shape=1,4,4,2,...

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-2026-59849

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-2026-59747

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...