FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess

ImpactAn input poolingratio that is smaller than 1 will trigger a heap OOB in tf.rawops.FractionalMaxPool and tf.rawops.FractionalAvgPool. PatchesWe have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48.The fix will be included in TensorFlow 2.11.0. We will also cherry...

PYSEC-2026-3383 FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess

Impact An input poolingratio that is smaller than 1 will trigger a heap OOB in tf.rawops.FractionalMaxPool and tf.rawops.FractionalAvgPool. Patches We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cher...

PYSEC-2026-3313 `FractionalMaxPoolGrad` Heap out of bounds read

Impact If FractionMaxPoolGrad is given outsize inputs rowpoolingsequence and colpoolingsequence, TensorFlow will crash. python import tensorflow as tf tf.rawops.FractionMaxPoolGrad originput = 1, 1, 1, 1, 1, origoutput = 1, 1, 1, outbackprop = 3, 3, 6, rowpoolingsequence = -0x4000000, 1, 1,...

`tf.raw_ops.Mfcc` crashes

ImpactIf ThreadUnsafeUnigramCandidateSampler is given input filterbankchannelcount greater than the allowed max size, TensorFlow will crash.pythonimport tensorflow as tftf.rawops.Mfcc spectrogram = 1.38, 6.32, 5.75, 9.51, samplerate = 2, upperfrequencylimit = 5.0, lowerfrequencylimit = 1.0,...

PYSEC-2026-3165 `FractionalMaxPoolGrad` Heap out of bounds read

Impact If FractionMaxPoolGrad is given outsize inputs rowpoolingsequence and colpoolingsequence, TensorFlow will crash. python import tensorflow as tf tf.rawops.FractionMaxPoolGrad originput = 1, 1, 1, 1, 1, origoutput = 1, 1, 1, outbackprop = 3, 3, 6, rowpoolingsequence = -0x4000000, 1, 1,...

PYSEC-2026-3245 TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`

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

PYSEC-2026-3372 TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`

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

PYSEC-2026-3250 TensorFlow vulnerable to `CHECK` fail in `FractionalMaxPoolGrad`

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 originput = tf.constant.453409232,...

PYSEC-2026-3375 TensorFlow vulnerable to `CHECK` fail in `FractionalMaxPoolGrad`

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 originput = tf.constant.453409232,...

TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`

ImpactIf QuantizedRelu or QuantizedRelu6 are given nonscalar inputs for minfeatures or maxfeatures, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfouttype = tf.quint8features = tf.constant28, shape=4,2, dtype=tf.quint8minfeatures =...

TensorFlow vulnerable to `CHECK` fail in `FractionalMaxPoolGrad`

ImpactFractionalMaxPoolGrad 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:pythonimport tensorflow as tfoverlapping = Trueoriginput = tf.constant.453409232,...

TensorFlow vulnerable to segfault in `QuantizedMatMul`

ImpactIf QuantizedMatMul is given nonscalar input for: - mina - maxa - minb - maxbIt gives a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfToutput = tf.qint32transposea = Falsetransposeb = FalseTactivation = tf.quint8a = tf.constant7, shape=3,4,...

TensorFlow vulnerable to `CHECK` fail in `FractionalMaxPoolGrad`

ImpactFractionalMaxPoolGrad 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:pythonimport tensorflow as tfoverlapping = Trueoriginput = tf.constant.453409232,...

TensorFlow vulnerable to segfault in `QuantizedBiasAdd`

ImpactIf QuantizedBiasAdd is given mininput, maxinput, minbias, maxbias tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfouttype = tf.qint32input = tf.constant85,170,255, shape=3, dtype=tf.quint8bias =...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`

ImpactIf 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.pythonimport tensorflow as tfnumbits = 8narrowrange = Falseinputs = tf.constant0, shape=2,3, dtype=tf.float32min = tf.constant0,...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`

ImpactIf 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.pythonimport tensorflow as tfnumbits = 8narrowrange = Falseinputs = tf.constant0, shape=2,3, dtype=tf.float32min = tf.constant0,...

PYSEC-2026-3199 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

Impact When tf.quantization.fakequantwithminmaxvarsperchannelgradient 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 arg0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None...

PYSEC-2026-3273 TensorFlow vulnerable to segfault in `QuantizedAvgPool`

Impact If QuantizedAvgPool is given mininput or maxinput 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,...

TensorFlow vulnerable to segfault in `QuantizedAvgPool`

ImpactIf QuantizedAvgPool is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfksize = 1, 2, 2, 1strides = 1, 2, 2, 1padding = "SAME"input = tf.constant1, shape=1,4,4,2,...

TensorFlow vulnerable to segfault in `QuantizedAvgPool`

ImpactIf QuantizedAvgPool is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfksize = 1, 2, 2, 1strides = 1, 2, 2, 1padding = "SAME"input = tf.constant1, shape=1,4,4,2,...