TensorFlow vulnerable to `CHECK` fail in `ParameterizedTruncatedNormal`

ImpactParameterizedTruncatedNormal 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.pythonimport tensorflow as tfseed = 1618seed2 = 0shape = tf.random.uniformshape=3, minval=-10000,...

TensorFlow vulnerable to `CHECK` fail in `ParameterizedTruncatedNormal`

ImpactParameterizedTruncatedNormal 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.pythonimport tensorflow as tfseed = 1618seed2 = 0shape = tf.random.uniformshape=3, minval=-10000,...

TensorFlow vulnerable to `CHECK` fail in `LRNGrad`

ImpactIf LRNGrad is given an outputimage input tensor that is not 4-D, it results in a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfdepthradius = 1bias = 1.59018219alpha = 0.117728651beta = 0.404427052inputgrads = tf.random.uniformshape=4, 4, 4, 4...

PYSEC-2026-3355 TensorFlow vulnerable to `CHECK` fail in `ParameterizedTruncatedNormal`

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,...

PYSEC-2026-3308 TensorFlow vulnerable to `CHECK` fail in `tf.linalg.matrix_rank`

Impact When tf.linalg.matrixrank 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.matrixranka=a Patches We have patched the issue in GitHub...

TensorFlow vulnerable to `CHECK` fail in `LRNGrad`

ImpactIf LRNGrad is given an outputimage input tensor that is not 4-D, it results in a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfdepthradius = 1bias = 1.59018219alpha = 0.117728651beta = 0.404427052inputgrads = tf.random.uniformshape=4, 4, 4, 4...

TensorFlow vulnerable to `CHECK` fail in `MaxPool`

ImpactWhen MaxPool receives a window size input array ksize with dimensions greater than its input tensor input, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as npinput = np.ones1, 1, 1, 1ksize = 1, 1, 2, 2strid...

TensorFlow vulnerable to `CHECK` fail in `MaxPool`

ImpactWhen MaxPool receives a window size input array ksize with dimensions greater than its input tensor input, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as npinput = np.ones1, 1, 1, 1ksize = 1, 1, 2, 2strid...

TensorFlow vulnerable to `CHECK` fail in `tf.linalg.matrix_rank`

ImpactWhen tf.linalg.matrixrank receives an empty input a, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfa = tf.constant, shape=0, 1, 1, dtype=tf.float32tf.linalg.matrixranka=a PatchesWe have patched the issue in GitHub commi...

PYSEC-2026-3343 TensorFlow vulnerable to `CHECK` fail in `MaxPool`

Impact When MaxPool receives a window size input array ksize with dimensions greater than its input tensor input, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np input = np.ones1, 1, 1, 1 ksize = 1, 1, 2, ...

PYSEC-2026-3147 TensorFlow vulnerable to `CHECK` fail in `LRNGrad`

Impact If LRNGrad is given an outputimage 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 depthradius = 1 bias = 1.59018219 alpha = 0.117728651 beta = 0.404427052 inputgrads = tf.random.uniformshape=4,...

PYSEC-2026-3213 TensorFlow vulnerable to `CHECK` fail in `Save` and `SaveSlices`

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"" tensornames = tf.constant"" Save data = tf.casttf.random.uniformshape=1,...

PYSEC-2026-3156 TensorFlow vulnerable to `CHECK` fail in `tf.linalg.matrix_rank`

Impact When tf.linalg.matrixrank 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.matrixranka=a Patches We have patched the issue in GitHub...

TensorFlow vulnerable to `CHECK` fail in `tf.linalg.matrix_rank`

ImpactWhen tf.linalg.matrixrank receives an empty input a, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfa = tf.constant, shape=0, 1, 1, dtype=tf.float32tf.linalg.matrixranka=a PatchesWe have patched the issue in GitHub commi...

PYSEC-2026-3219 TensorFlow vulnerable to `CHECK` fail in `ParameterizedTruncatedNormal`

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,...

TensorFlow vulnerable to segfault in `SparseBincount`

ImpactIf SparseBincount is given inputs for indices, values, and denseshape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfbinaryoutput = Trueindices = tf.random.uniformshape=, minval=-10000,...

PYSEC-2026-3205 TensorFlow vulnerable to `CHECK` fail in `MaxPool`

Impact When MaxPool receives a window size input array ksize with dimensions greater than its input tensor input, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np input = np.ones1, 1, 1, 1 ksize = 1, 1, 2, ...

PYSEC-2026-3303 TensorFlow vulnerable to `CHECK` fail in `LRNGrad`

Impact If LRNGrad is given an outputimage 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 depthradius = 1 bias = 1.59018219 alpha = 0.117728651 beta = 0.404427052 inputgrads = tf.random.uniformshape=4,...

PYSEC-2026-3246 TensorFlow vulnerable to segfault in `QuantizeDownAndShrinkRange`

Impact If QuantizeDownAndShrinkRange is given nonscalar inputs for inputmin or inputmax, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outtype = tf.quint8 input = tf.constant1, shape=3, dtype=tf.qint32 inputmin = tf.constant,...

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 =...