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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•18 views

PT-2026-59911

Impact tf.keras.losses.poisson receives a y pred and y true 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 true value =...

7.5CVSS7AI score0.00474EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•22 views

PT-2026-59903

Impact When running on GPU, tf.image.generate bounding box proposals 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 tf.image.generate bounding box...

7.5CVSS6.9AI score0.00473EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•16 views

PT-2026-59959

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
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•16 views

PT-2026-59778

Impact The function MakeGrapplerFunctionItem takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. Patches We have patched the issue in GitHub commit...

9.1CVSS7AI score0.00474EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•25 views

PT-2026-59924

Impact The function MakeGrapplerFunctionItem takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. Patches We have patched the issue in GitHub commit...

9.1CVSS7AI score0.00474EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•19 views

PT-2026-59886

Impact NPE in QuantizedMatMulWithBiasAndDequantize with MKL enable python import tensorflow as tf func = tf.raw ops.QuantizedMatMulWithBiasAndDequantize para='a': tf.constant138, dtype=tf.quint8, 'b': tf.constant4, dtype=tf.qint8, 'bias': 31.81644630432129, 47.21876525878906, 109.95201110839844,...

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

PT-2026-59998

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.extract volume patches by passing in quantized tensors as input ksizes. python import numpy as np import...

7.5CVSS7AI score0.00435EPSS
SaveExploits1References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•26 views

PT-2026-59894

Impact Constructing a tflite model with a paramater filter input channel of less than 1 gives a FPE. Patches We have patched the issue in GitHub commit 34f8368c535253f5c9cb3a303297743b62442aaa. The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1...

7.5CVSS6.7AI score0.00394EPSS
SaveExploits0References7
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•12 views

PT-2026-59852

Impact If the stride and window size are not positive for tf.raw ops.AvgPoolGrad, it can give an FPE. python import tensorflow as tf import numpy as np @tf.functionjit compile=True def test: y = tf.raw ops.AvgPoolGradorig input shape=1,0,0,0, grad=0.39117979, ksize=1,0,0,0, strides=1,0,0,0,...

7.5CVSS6.6AI score0.00394EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•20 views

PT-2026-59891

Impact When SparseSparseMaximum is given invalid sparse tensors as inputs, it can give an NPE. python import tensorflow as tf tf.raw ops.SparseSparseMaximum a indices=1, a values = 0.1 , a shape = 2, b indices=, b values =2 , b shape = 2, Patches We have patched the issue in GitHub commit...

7.5CVSS6.6AI score0.00443EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•17 views

PT-2026-59931

Impact version:2.11.0 //core/ops/audio ops.cc:70 Status SpectrogramShapeFnInferenceContext c ShapeHandle input; TF RETURN IF ERRORc-WithRankc-input0, 2, &input; int32 t window size; TF RETURN IF ERRORc-GetAttr"window size", &window size; int32 t stride; TF RETURN IF ERRORc-GetAttr"stride", &strid...

7.5CVSS6.6AI score0.00387EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•16 views

PT-2026-59747

Impact TFversion 2.11.0 //tensorflow/core/ops/array ops.cc:1067 const Tensor hypothesis shape t = c-input tensor2; std::vector dimshypothesis shape t-NumElements - 1; for int i = 0; i MakeDimstd::maxh valuesi, t valuesi; if hypothesis shape t is empty, hypothesis shape t-NumElements - 1 will be...

7.5CVSS6.6AI score0.00394EPSS
SaveExploits0References7
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•17 views

PT-2026-59789

Impact When CollectiveGather receives an scalar input input, it gives a CHECK fails that can be used to trigger a denial of service attack. python import tensorflow as tf arg 0=1 arg 1=1 arg 2=1 arg 3=1 arg 4=3, 3,3 arg 5='auto' arg 6=0 arg 7='' tf.raw ops.CollectiveGatherinput=arg 0, group...

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

PT-2026-59183

Improper buffer restrictions in the IntelR Optimization for Tensorflow software before version 2.12 may allow an authenticated user to potentially enable escalation of privilege via local access...

7.8CVSS7AI score0.0016EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•21 views

PT-2026-59845

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...

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

PT-2026-59767

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 num bits = 8 narrow range = False inputs = tf.constant0, shape=2,3, dtype=tf.float32 min = tf.constant...

7.5CVSS6.9AI score0.00462EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•12 views

PT-2026-59922

Impact When tf.linalg.matrix rank 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.matrix ranka=a Patches We have patched the issue in GitH...

7.5CVSS6.9AI score0.00488EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•29 views

PT-2026-59745

Impact When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process. python import tensorflow as tf class QuantConv2DTransposedtf.keras.layers.Layer: def buildself, input shape: self.kernel = self.add weight"kernel", 3, 3,...

7.5CVSS6.9AI score0.00765EPSS
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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•22 views

PT-2026-59769

Impact If FakeQuantWithMinMaxVarsPerChannel is given min or max tensors of a rank other than one, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf num bits = 8 narrow range = False inputs = tf.constant0, shape=4, dtype=tf.float32 mi...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•15 views

PT-2026-59865

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 orig input = tf.constant.453409232,...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
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