PYSEC-2026-3261 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-2026-3165 `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-2026-3369 `tf.raw_ops.Mfcc` crashes

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

PYSEC-2026-3239 `tf.raw_ops.Mfcc` crashes

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

PYSEC-2026-3284 `CHECK_EQ` fail in `tf.raw_ops.TensorListResize`

Impact If tf.rawops.TensorListResize is given a nonscalar value for input size, it results CHECK fail which can be used to trigger a denial of service attack. python import numpy as np import tensorflow as tf a = datastructures.tftensorlistnewelements = tf.constantvalue=3, 4, 5 b = np.zeros0, 2, ...

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,...

PYSEC-2026-3283 Segfault in `tf.raw_ops.TensorListConcat`

Impact If tf.rawops.TensorListConcat is given elementshape=, it results segmentation fault which can be used to trigger a denial of service attack. python import tensorflow as tf tf.rawops.TensorListConcat inputhandle=tf.data.experimental.tovarianttf.data.Dataset.fromtensorslices1, 2, 3,...

PYSEC-2026-3118 `CHECK_EQ` fail in `tf.raw_ops.TensorListResize`

Impact If tf.rawops.TensorListResize is given a nonscalar value for input size, it results CHECK fail which can be used to trigger a denial of service attack. python import numpy as np import tensorflow as tf a = datastructures.tftensorlistnewelements = tf.constantvalue=3, 4, 5 b = np.zeros0, 2, ...

PYSEC-2026-3192 `MirrorPadGrad` heap out of bounds read

Impact If MirrorPadGrad is given outsize input paddings, TensorFlow will give a heap OOB error. python import tensorflow as tf tf.rawops.MirrorPadGradinput=1, paddings=0x77f00000,0xa000000, mode = 'REFLECT' Patches We have patched the issue in GitHub commit 717ca98d8c3bba348ff62281fdf38dcb5ea1ec9...

PYSEC-2026-3332 `MirrorPadGrad` heap out of bounds read

Impact If MirrorPadGrad is given outsize input paddings, TensorFlow will give a heap OOB error. python import tensorflow as tf tf.rawops.MirrorPadGradinput=1, paddings=0x77f00000,0xa000000, mode = 'REFLECT' Patches We have patched the issue in GitHub commit 717ca98d8c3bba348ff62281fdf38dcb5ea1ec9...

PYSEC-2026-3117 Segfault in `tf.raw_ops.TensorListConcat`

Impact If tf.rawops.TensorListConcat is given elementshape=, it results segmentation fault which can be used to trigger a denial of service attack. python import tensorflow as tf tf.rawops.TensorListConcat inputhandle=tf.data.experimental.tovarianttf.data.Dataset.fromtensorslices1, 2, 3,...

PYSEC-2026-3136 Overflow in `tf.keras.losses.poisson`

Impact tf.keras.losses.poisson receives a ypred and ytrue 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 truevalue =...

PYSEC-2026-3384 Segfault via invalid attributes in `pywrap_tfe_src.cc`

Impact If a list of quantized tensors is assigned to an attribute, the pywrap code fails to parse the tensor and returns a nullptr, which is not caught. An example can be seen in tf.compat.v1.extractvolumepatches by passing in quantized tensors as input ksizes. python import numpy as np import...

PYSEC-2026-3194 `CHECK` fail in `BCast` overflow

Impact If BCast::ToShape is given input larger than an int32, it will crash, despite being supposed to handle up to an int64. An example can be seen in tf.experimental.numpy.outer by passing in large input to the input b. python import tensorflow as tf value = tf.constantshape=2, 1024, 1024, 1024...

PYSEC-2026-3262 Segfault via invalid attributes in `pywrap_tfe_src.cc`

Impact If a list of quantized tensors is assigned to an attribute, the pywrap code fails to parse the tensor and returns a nullptr, which is not caught. An example can be seen in tf.compat.v1.extractvolumepatches by passing in quantized tensors as input ksizes. python import numpy as np import...

PYSEC-2026-3297 Overflow in `tf.keras.losses.poisson`

Impact tf.keras.losses.poisson receives a ypred and ytrue 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 truevalue =...

PYSEC-2026-3333 `CHECK` fail in `BCast` overflow

Impact If BCast::ToShape is given input larger than an int32, it will crash, despite being supposed to handle up to an int64. An example can be seen in tf.experimental.numpy.outer by passing in large input to the input b. python import tensorflow as tf value = tf.constantshape=2, 1024, 1024, 1024...

PYSEC-2026-3288 FPE in `tf.image.generate_bounding_box_proposals`

Impact When running on GPU, tf.image.generateboundingboxproposals receives a scores input that must be of rank 4 but is not checked. python import tensorflow as tf a = tf.constantvalue=1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 b = tf.constantvalue=1...

PYSEC-2026-3124 FPE in `tf.image.generate_bounding_box_proposals`

Impact When running on GPU, tf.image.generateboundingboxproposals receives a scores input that must be of rank 4 but is not checked. python import tensorflow as tf a = tf.constantvalue=1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 b = tf.constantvalue=1...

PYSEC-2026-3275 Overflow in `ImageProjectiveTransformV2`

Impact When tf.rawops.ImageProjectiveTransformV2 is given a large output shape, it overflows. python import tensorflow as tf interpolation = "BILINEAR" fillmode = "REFLECT" images = tf.constant0.184634328, shape=2,5,8,3, dtype=tf.float32 transforms = tf.constant0.378575385, shape=2,8,...

PYSEC-2026-3345 Seg fault in `ndarray_tensor_bridge` due to zero and large inputs

Impact If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error: python np.ones0, 231, 231 An example of a proof of concept: python import numpy as np import tensorflow as tf inputval =...

PYSEC-2026-3208 Seg fault in `ndarray_tensor_bridge` due to zero and large inputs

Impact If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error: python np.ones0, 231, 231 An example of a proof of concept: python import numpy as np import tensorflow as tf inputval =...

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-2026-3126 Overflow in `FusedResizeAndPadConv2D`

Impact When tf.rawops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows. python import tensorflow as tf mode = "REFLECT" strides = 1, 1, 1, 1 padding = "SAME" resizealigncorners = False input = tf.constant147, shape=3,3,1,1, dtype=tf.float16 size =...

PYSEC-2026-3290 Overflow in `FusedResizeAndPadConv2D`

Impact When tf.rawops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows. python import tensorflow as tf mode = "REFLECT" strides = 1, 1, 1, 1 padding = "SAME" resizealigncorners = False input = tf.constant147, shape=3,3,1,1, dtype=tf.float16 size =...

PYSEC-2026-3079 OpenStack Sushy-Tools and VirtualBMC Improper Preservation of Permissions

An issue was discovered in OpenStack Sushy-Tools through 0.21.0 and VirtualBMC through 2.2.2. Changing the boot device configuration with these packages removes password protection from the managed libvirt XML domain. NOTE: this only affects an "unsupported, production-like configuration."...

PYSEC-2026-3251 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-2026-3105 Overflow in `ImageProjectiveTransformV2`

Impact When tf.rawops.ImageProjectiveTransformV2 is given a large output shape, it overflows. python import tensorflow as tf interpolation = "BILINEAR" fillmode = "REFLECT" images = tf.constant0.184634328, shape=2,5,8,3, dtype=tf.float32 transforms = tf.constant0.378575385, shape=2,8,...

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-2026-3156 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...

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-2026-3355 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-2026-3213 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-2026-3219 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-2026-3205 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-2026-3343 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-2026-3308 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-2026-3303 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-2026-3270 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-2026-3285 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-2026-3250 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-2026-3372 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-2026-3373 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-2026-3246 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,...

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-2026-3093 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-2026-3245 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-2026-3375 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-2026-3150 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-2026-3360 TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`

Impact The implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf strides = 1, 1, 1, 1 padding = "SAME" usecudnnongpu = True explicitpaddings =...