150 matches found
TensorFlow has Null Pointer Error in RandomShuffle with XLA enable
ImpactNPE in RandomShuffle with XLA enable pythonimport tensorflow as tffunc = tf.rawops.RandomShufflepara = 'value': 1e+20, 'seed': -4294967297, 'seed2': [email protected]=Truedef test: y = funcpara return ytest PatchesWe have patched the issue in GitHub commit...
Invalid char to bool conversion when printing a tensor
ImpactWhen printing a tensor, we get it's data as a const char array since that's the underlying storage and then we typecast it to the element type. However, conversions from char to bool are undefined if the char is not 0 or 1, so sanitizers/fuzzers will crash. PatchesWe have patched the issue ...
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs
ImpactIf 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:pythonnp.ones0, 231, 231An example of a proof of concept:pythonimport numpy as npimport tensorflow as tfinputval =...
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, ...
TensorFlow vulnerable to `CHECK` fail in `AudioSummaryV2`
ImpactWhen AudioSummaryV2 receives an input samplerate with more than one element, it gives a CHECK fails that can be used to trigger a denial of service attack.pythonimport tensorflow as tfarg0=''arg1=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=Nonearg2=tf.random.uniformshape=2,1,...
PT-2026-59878
Impact The implementation of AvgPoolGrad does not fully validate the input orig input shape. 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" data format = "NHWC" orig...
PT-2026-59975
Impact If Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np with tf.device"CPU": also can...
PT-2026-59940
Impact If QuantizedInstanceNorm is given x min or x max 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 output range given = False given y min = 0 given y max = 0 variance epsilon = 1e-05 min separation =...
PT-2026-59974
Impact The implementation of Conv2DBackpropInput requires input sizes 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" use cudnn on gpu = True explicit paddings =...
PT-2026-59954
Impact If SparseFillEmptyRowsGrad is given empty inputs, TensorFlow will crash. python import tensorflow as tf tf.raw ops.SparseFillEmptyRowsGrad reverse index map=, grad values=, name=None Patches We have patched the issue in GitHub commit af4a6a3c8b95022c351edae94560acc61253a1b8. The fix will b...
Incomplete validation in signal ops leads to crashes in TensorFlow
ImpactThe tf.compat.v1.signal.rfft2d and tf.compat.v1.signal.rfft3d lack input validation and under certain condition can result in crashes due to CHECK-failures. Patches We have patched the issue in GitHub commit 0a8a781e597b18ead006d19b7d23d0a369e9ad73 merging GitHub PR 55274.The fix will be...
PYSEC-2026-3269 TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
Impact When Conv2DBackpropInput receives empty outbackprop inputs e.g. 3, 1, 0, 1, the current CPU/GPU kernels CHECK fail one with dnnl, the other with cudnn. This can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np inputsizes = 3, 1, 1, 2 filter =...
Missing validation causes denial of service via `StagePeek`
ImpactThe implementation of tf.rawops.StagePeek does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfindex = tf.constant, shape=0, dtype=tf.int32tf.rawops.StagePeekindex=index,...
PYSEC-2026-3179 Missing validation causes denial of service via `GetSessionTensor`
Impact The implementation of tf.rawops.GetSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf handle = tf.constant"", shape=0, dtype=tf.string...
PYSEC-2026-945 Overflow in `ResizeNearestNeighborGrad`
Impact When tf.rawops.ResizeNearestNeighborGrad is given a large size input, it overflows. import tensorflow as tf aligncorners = True halfpixelcenters = False grads = tf.constant1, shape=1,8,16,3, dtype=tf.float16 size = tf.constant1879048192,1879048192, shape=2, dtype=tf.int32...
`CHECK` fail via inputs in `SparseFillEmptyRowsGrad`
ImpactIf SparseFillEmptyRowsGrad is given empty inputs, TensorFlow will crash.pythonimport tensorflow as tftf.rawops.SparseFillEmptyRowsGrad reverseindexmap=, gradvalues=, name=None PatchesWe have patched the issue in GitHub commit af4a6a3c8b95022c351edae94560acc61253a1b8.The fix will be included...
PYSEC-2026-979 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-2026-1002 Missing validation crashes `QuantizeAndDequantizeV4Grad`
Impact The implementation of tf.rawops.QuantizeAndDequantizeV4Grad does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf tf.rawops.QuantizeAndDequantizeV4Grad gradients=tf.constant1,...
Missing validation causes denial of service via `LSTMBlockCell`
ImpactThe implementation of tf.rawops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tftf.rawops.LSTMBlockCell x=tf.constant0.837607, shape=28,29, dtype=tf.float32,...
