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OSV
OSV
•added 2026/07/13 2:19 p.m.•17 views

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 =...

5.9CVSS7AI score0.00478EPSS
SaveExploits0References7
PyPA
PyPA
•added 2026/07/13 2:19 p.m.•21 views

TensorFlow vulnerable to `CHECK` failures in `AvgPool3DGrad`

ImpactThe implementation of AvgPool3DGradOp does not fully validate the input originputshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfksize = 1, 1, 1, 1, 1strides = 1, 1, 1, 1, 1padding =...

7.5CVSS7AI score0.00462EPSS
SaveExploits0References7Affected Software1
OSV
OSV
•added 2026/07/13 2:19 p.m.•16 views

PYSEC-2026-3257 TensorFlow vulnerable to `CHECK` failures in `AvgPool3DGrad`

Impact The implementation of AvgPool3DGradOp does not fully validate the input originputshape. 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 ksize = 1, 1, 1, 1, 1 strides = 1, 1, 1, 1, 1 padding ...

5.9CVSS7AI score0.00462EPSS
SaveExploits0References7
OSV
OSV
•added 2026/07/13 2:19 p.m.•15 views

PYSEC-2026-3311 TensorFlow vulnerable to `CHECK` fail in `RandomPoissonV2`

Impact When RandomPoissonV2 receives large input shape and rates, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=4,, dtype=tf.int32, maxval=65536 arg1=tf.random.uniformshape=4, 4, 4, 4, 4, dtype=tf.float32, maxval=None...

5.9CVSS6.9AI score0.00478EPSS
SaveExploits0References7
PyPA
PyPA
•added 2026/07/13 2:19 p.m.•28 views

TensorFlow vulnerable to `CHECK` fail in `DenseBincount`

ImpactDenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfbinaryoutput = Trueinput =...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References7Affected Software1
OSV
OSV
•added 2026/07/13 2:19 p.m.•15 views

PYSEC-2026-3377 TensorFlow vulnerable to `CHECK` fail in `DenseBincount`

Impact DenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf binaryoutput = True input =...

5.9CVSS6.1AI score0.00478EPSS
SaveExploits0References7
PyPA
PyPA
•added 2026/07/13 2:19 p.m.•23 views

TensorFlow vulnerable to `CHECK` fail in `DenseBincount`

ImpactDenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfbinaryoutput = Trueinput =...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References7Affected Software1
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•18 views

PT-2026-59994

Impact The implementation of AvgPool3DGradOp does not fully validate the input orig input shape. 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 ksize = 1, 1, 1, 1, 1 strides = 1, 1, 1, 1, 1 paddin...

7.5CVSS7AI score0.00462EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•29 views

PT-2026-59921

Impact When TensorListFromTensor receives an element shape of a rank greater than one, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg 0=tf.random.uniformshape=6, 6, 2, dtype=tf.bfloat16, maxval=None arg 1=tf.random.uniformshape=6, 9, 1, 3,...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•25 views

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...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•17 views

PT-2026-59735

Impact If tf.raw ops.TensorListConcat is given element shape=, it results segmentation fault which can be used to trigger a denial of service attack. python import tensorflow as tf tf.raw ops.TensorListConcat input handle=tf.data.experimental.to varianttf.data.Dataset.from tensor slices1, 2, 3,...

7.5CVSS6.9AI score0.00463EPSS
SaveExploits1References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•32 views

PT-2026-59872

Impact The implementation of AvgPool3DGradOp does not fully validate the input orig input shape. 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 ksize = 1, 1, 1, 1, 1 strides = 1, 1, 1, 1, 1 paddin...

7.5CVSS7AI score0.00462EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•16 views

PT-2026-59947

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...

7.5CVSS6.9AI score0.00473EPSS
SaveExploits1References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•19 views

PT-2026-59741

Impact When running with XLA, tf.raw ops.ParallelConcat segfaults with a nullptr dereference when given a parameter shape with rank that is not greater than zero. python import tensorflow as tf func = tf.raw ops.ParallelConcat para = 'shape': 0, 'values': 1 @tf.functionjit compile=True def test: ...

7.5CVSS6.6AI score0.00394EPSS
SaveExploits0References7
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•16 views

PT-2026-59825

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 input val ...

7.5CVSS6.9AI score0.00355EPSS
SaveExploits1References7
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•17 views

PT-2026-59702

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...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•20 views

PT-2026-59991

Impact DenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf binary output = True input =...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•19 views

PT-2026-59836

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,...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•17 views

PT-2026-59910

Impact The implementation of FractionalAvgPoolGrad does not fully validate the input orig input tensor shape. 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 orig input tensor...

7.5CVSS7AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•17 views

PT-2026-59969

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,...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
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