PYSEC-2026-3349 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-2026-3376 Out of bounds segmentation fault due to unequal op inputs in Tensorflow

Impact tf.rawops.DynamicStitch specifies input sizes when it is registered. cpp REGISTEROP"DynamicStitch" .Input"indices: N int32" .Input"data: N T" .Output"merged: T" .Attr"N : int = 1" .Attr"T : type" .SetShapeFnDynamicStitchShapeFunction; When it receives a differing number of inputs, such as...

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...

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,...

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,...

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-2026-3250 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-2026-3119 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-2026-3305 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`

Impact If 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. python import tensorflow as tf numbits = 8 narrowrange = False inputs = tf.constant0, shape=2,3, dtype=tf.float32 min = tf.constant0,...

PYSEC-2026-3150 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`

Impact If 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. python import tensorflow as tf numbits = 8 narrowrange = False inputs = tf.constant0, shape=2,3, dtype=tf.float32 min = tf.constant0,...

PYSEC-2026-3101 TensorFlow vulnerable to segfault in `QuantizedBiasAdd`

Impact If 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. python import tensorflow as tf outtype = tf.qint32 input = tf.constant85,170,255, shape=3, dtype=tf.quint8 bias =...

PYSEC-2026-3263 TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. 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" dataformat = "NHWC"...

PYSEC-2026-3103 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,...

PYSEC-2026-3244 TensorFlow vulnerable to segfault in `QuantizedAdd`

Impact If QuantizedAdd 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 Toutput = tf.qint32 x = tf.constant140, shape=1, dtype=tf.quint8 y = tf.constant26, shape=10,...

PYSEC-2026-3083 TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. 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" dataformat = "NHWC"...

PYSEC-2026-3155 TensorFlow vulnerable to `CHECK` fail in `TensorListFromTensor`

Impact When TensorListFromTensor receives an elementshape of a rank greater than one, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=6, 6, 2, dtype=tf.bfloat16, maxval=None arg1=tf.random.uniformshape=6, 9, 1, 3,...

PYSEC-2026-3233 TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`

Impact If LowerBound or UpperBound is given an emptysortedinputs 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 outtype = tf.int32 sortedinputs = tf.constant, shape=10,0, dtype=tf.float32...

PYSEC-2026-3255 TensorFlow vulnerable to `CHECK` fail in `SetSize`

Impact When SetSize receives an input setshape that is not a 1D tensor, it gives a CHECK fails that can be used to trigger a denial of service attack. python import tensorflow as tf arg0=1 arg1=1,1 arg2=1 arg3=True arg4='' tf.rawops.SetSizesetindices=arg0, setvalues=arg1, setshape=arg2,...

PYSEC-2026-3133 TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`

Impact The implementation of FractionalAvgPoolGrad does not fully validate the input originputtensorshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack. python import tensorflow as tf overlapping = True originputtensorshape =...