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-2026-3303 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 `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,...

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 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,...

PYSEC-2026-3373 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,...

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,...

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 segfault in `QuantizeDownAndShrinkRange`

ImpactIf 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.pythonimport tensorflow as tfouttype = tf.quint8input = tf.constant1, shape=3, dtype=tf.qint32inputmin = tf.constant, shape=0,...

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,...

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-2026-3119 TensorFlow vulnerable to segfault in `QuantizedMatMul`

Impact If QuantizedMatMul is given nonscalar input for: - mina - maxa - minb - maxb It gives a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 transposea = False transposeb = False Tactivation = tf.quint8 a = tf.constant7,...

PYSEC-2026-3285 TensorFlow vulnerable to segfault in `QuantizedMatMul`

Impact If QuantizedMatMul is given nonscalar input for: - mina - maxa - minb - maxb It gives a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 transposea = False transposeb = False Tactivation = tf.quint8 a = tf.constant7,...

TensorFlow vulnerable to segfault in `QuantizeDownAndShrinkRange`

ImpactIf 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.pythonimport tensorflow as tfouttype = tf.quint8input = tf.constant1, shape=3, dtype=tf.qint32inputmin = tf.constant, shape=0,...

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 `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,...

PYSEC-2026-3093 TensorFlow vulnerable to segfault in `SparseBincount`

Impact If 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. python import tensorflow as tf binaryoutput = True indices = tf.random.uniformshape=, minval=-10000...

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...