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Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•3 views

PT-2026-59964

Impact The implementation of tf.raw ops.SparseTensorToCSRSparseMatrix 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 indices = tf.constant53, shape=3, dtype=tf.int64 values =...

5.5CVSS5.7AI score0.00325EPSS
SaveExploits1References12
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•3 views

PT-2026-59837

Impact If tf.sparse.cross receives an input separator that is not a scalar, it gives a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf tf.sparse.crossinputs=,name='a',separator=tf.constant'a', 'b',dtype=tf.string Patches We have patched the issue ...

7.5CVSS7.2AI score0.00488EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•5 views

PT-2026-59840

Impact The implementation of SparseTensorSliceDataset has an undefined behavior: under certain condition it can be made to dereference a nullptr value: python import tensorflow as tf import numpy as np tf.raw ops.SparseTensorSliceDataset indices=, values=, dense shape=1,1 The 3 input arguments...

7.6CVSS6.3AI score0.00752EPSS
SaveExploits1References10
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•4 views

PT-2026-59761

Impact The implementation of SobolSampleOp is vulnerable to a denial of service via CHECK-failure assertion failure caused by assuming input0, input1, and input2 to be scalar. python import tensorflow as tf tf.raw ops.SobolSampledim=tf.constant1,0, num results=tf.constant1, skip=tf.constant1...

7.5CVSS7.2AI score0.00531EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•4 views

PT-2026-59820

Impact The implementation of tf.raw ops.UnsortedSegmentJoin 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.strings.unsorted segment join inputs='123', segment ids=0, num...

5.5CVSS5.7AI score0.00354EPSS
SaveExploits1References14
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•8 views

PT-2026-59777

Impact The implementation of OpLevelCostEstimator::CalculateTensorSize is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements: cc int64 t OpLevelCostEstimator::CalculateTensorSize const OpInfo::TensorProperties...

6.5CVSS6.6AI score0.00789EPSS
SaveExploits1References10
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•5 views

PT-2026-59950

Impact The implementation of tf.raw ops.DeleteSessionTensor 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 tf.raw...

5.5CVSS5.7AI score0.00333EPSS
SaveExploits1References12
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•5 views

PT-2026-59817

Impact The TensorKey hash function used total estimated AllocatedBytes, which a is an estimate per tensor, and b is a very poor hash function for constants e.g. int32 t. It also tried to access individual tensor bytes through tensor.data of size AllocatedBytes. This led to ASAN failures because t...

5.5CVSS5.9AI score0.0023EPSS
SaveExploits0References10
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•6 views

PT-2026-59718

Impact An attacker can craft a TFLite model that would allow limited reads and writes outside of arrays in TFLite. This exploits missing validation in the conversion from sparse tensors to dense tensors. Patches We have patched the issue in GitHub commit 6364463d6f5b6254cac3d6aedf999b6a96225038...

8.8CVSS7.4AI score0.00844EPSS
SaveExploits1References10
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•6 views

PT-2026-59926

Impact The implementation of tf.ragged.constant does not fully validate the input arguments. This results in a denial of service by consuming all available memory: python import tensorflow as tf tf.ragged.constantpylist=,ragged rank=8968073515812833920 Patches We have patched the issue in GitHub...

5.5CVSS5.7AI score0.00324EPSS
SaveExploits1References13
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•7 views

PT-2026-59792

Impact The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a SavedModel such that IsSimplifiableReshape would trigger CHECK failures. Patches We have patched the issue in GitHub commits ebc1a2ffe5a7573d905e99bd0ee3568ee07c12c1,...

6.5CVSS6.5AI score0.0116EPSS
SaveExploits1References12
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•5 views

PT-2026-59727

Impact The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a SavedModel such that SafeToRemoveIdentity would trigger CHECK failures. Patches We have patched the issue in GitHub commit 92dba16749fae36c246bec3f9ba474d9ddeb7662. The fix will be included in...

6.5CVSS6.5AI score0.00828EPSS
SaveExploits1References10
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•4 views

PT-2026-59857

Impact The estimator for the cost of some convolution operations can be made to execute a division by 0: python import tensorflow as tf @tf.function def test: y=tf.raw ops.AvgPoolGrad orig input shape=1,1,1,1, grad=1.0,1.0,1.0,2.0,2.0,2.0,3.0,3.0,3.0, ksize=1,1,1,1, strides=1,1,1,0,...

6.5CVSS6.7AI score0.00789EPSS
SaveExploits1References10
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•4 views

PT-2026-59723

Impact There is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1. ops which don't yet have support for quantized types added after migration to TF 2.x: python import numpy as np import tensorflow as tf tf.compat.v1.placeholder with...

5.5CVSS5.7AI score0.00325EPSS
SaveExploits1References13
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•3 views

PT-2026-59938

Impact The implementation of tf.raw ops.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 tf.raw...

5.5CVSS5.7AI score0.00359EPSS
SaveExploits1References12
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•4 views

PT-2026-59706

Impact The implementation of tf.raw ops.TensorSummaryV2 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 numpy as np import tensorflow as tf tf.raw ops.TensorSummaryV2 tag=np.array'test',...

5.5CVSS5.7AI score0.00325EPSS
SaveExploits1References12
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•3 views

PT-2026-59770

Impact When decoding a tensor from protobuf, TensorFlow might do a null-dereference if attributes of some mutable arguments to some operations are missing from the proto. This is guarded by a DCHECK: cc const auto attr = attrs.Findarg-s; DCHECKattr != nullptr; if attr-value case == AttrValue::kLi...

6.5CVSS6.7AI score0.01EPSS
SaveExploits1References10
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•5 views

PT-2026-59731

Impact Multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid: python import tensorflow as tf tf.raw ops.QueueIsClosedV2handle= python import tensorflow as tf tf.summary.flushwriter= In graph mode, it would have been impossible to perform these...

5.5CVSS5.5AI score0.00325EPSS
SaveExploits1References12
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•7 views

PT-2026-59841

Impact The implementation of tf.raw ops.QuantizedConv2D does not fully validate the input arguments: python import tensorflow as tf input = tf.constant1, shape=1, 2, 3, 3, dtype=tf.quint8 filter = tf.constant1, shape=1, 2, 3, 3, dtype=tf.quint8 bad args min input = tf.constant, shape=0,...

5.5CVSS5.8AI score0.00341EPSS
SaveExploits1References12
Positive Technologies
Positive Technologies
•added 2026/07/09 12:00 a.m.•3 views

PT-2026-59889

Impact There is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1. ops which don't yet have support for quantized types added after migration to TF 2.x: python import numpy as np import tensorflow as tf tf.compat.v1.placeholder with...

5.5CVSS5.7AI score0.00325EPSS
SaveExploits1References13
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