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Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•19 views

PT-2026-59793

Impact Integer overflow occurs when 2^31 = num frames height width channels 2^32, for example Full HD screencast of at least 346 frames. python import urllib.request dat =...

7.5CVSS6.7AI score0.00308EPSS
SaveExploits0References7
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•31 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-2026-59779

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 arg 0=tf.random.uniformshape=4,, dtype=tf.int32, maxval=65536 arg 1=tf.random.uniformshape=4, 4, 4, 4, 4, dtype=tf.float32, maxval=No...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•22 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.•20 views

PT-2026-59980

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
SaveExploits0References7
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•15 views

PT-2026-59871

Impact If Requantize is given input min, input max, requested output min, requested output 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 out type = tf.quint8 input = tf.constant1, shape=3,...

7.5CVSS6.9AI score0.0051EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•18 views

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 =...

7.5CVSS6.9AI score0.00462EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•25 views

PT-2026-59914

Impact If the parameter indices for DynamicStitch does not match the shape of the parameter data, it can trigger an stack OOB read. python import tensorflow as tf func = tf.raw ops.DynamicStitch para='indices': 0xdeadbeef, 405, 519, 758, 1015, 'data': 110.27793884277344, 120.29475402832031,...

7.5CVSS6.6AI score0.00394EPSS
SaveExploits0References7
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•11 views

PT-2026-59705

Impact Inputs dense features or example state data not of rank 2 will trigger a CHECK fail in SdcaOptimizer. python import tensorflow as tf tf.raw ops.SdcaOptimizer sparse example indices=4 tf.random.uniform5,5,5,3, dtype=tf.dtypes.int64, maxval=100, sparse feature indices=4...

7.5CVSS6.9AI score0.00474EPSS
SaveExploits1References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•14 views

PT-2026-59968

Impact When tf.random.gamma receives large input shape and rates, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg 0=tf.random.uniformshape=4,, dtype=tf.int32, maxval=65536 arg 1=tf.random.uniformshape=4, 4, dtype=tf.float64, maxval=None arg...

7.5CVSS6.9AI score0.00488EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•15 views

PT-2026-59936

Impact Eig can be fed an incorrect Tout input, resulting in a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg 0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2, dtype=tf.float32 arg 1=tf.complex128 arg 2=True arg 3='' tf.raw...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•22 views

PT-2026-59860

Impact If QuantizedRelu or QuantizedRelu6 are given nonscalar inputs for min features or max features, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf out type = tf.quint8 features = tf.constant28, shape=4,2, dtype=tf.quint8 min...

7.5CVSS6.9AI score0.0051EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•30 views

PT-2026-59870

Impact When SetSize receives an input set shape that is not a 1D tensor, 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=1,1 arg 2=1 arg 3=True arg 4='' tf.raw ops.SetSizeset indices=arg 0, set values=arg 1, set shape=arg...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•16 views

PT-2026-59877

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.•14 views

PT-2026-59993

Impact If Requantize is given input min, input max, requested output min, requested output 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 out type = tf.quint8 input = tf.constant1, shape=3,...

7.5CVSS6.9AI score0.0051EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•13 views

PT-2026-59992

Impact When SetSize receives an input set shape that is not a 1D tensor, 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=1,1 arg 2=1 arg 3=True arg 4='' tf.raw ops.SetSizeset indices=arg 0, set values=arg 1, set shape=arg...

7.5CVSS6.9AI score0.00478EPSS
SaveExploits0References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•13 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.•21 views

PT-2026-59879

Impact Inputs dense features or example state data not of rank 2 will trigger a CHECK fail in SdcaOptimizer. python import tensorflow as tf tf.raw ops.SdcaOptimizer sparse example indices=4 tf.random.uniform5,5,5,3, dtype=tf.dtypes.int64, maxval=100, sparse feature indices=4...

7.5CVSS6.9AI score0.00474EPSS
SaveExploits1References8
Positive Technologies
Positive Technologies
•added 2026/07/13 12:00 a.m.•31 views

PT-2026-59912

Impact When the BaseCandidateSamplerOp function receives a value in true classes larger than range max, a heap oob vuln occurs. python tf.raw ops.ThreadUnsafeUnigramCandidateSampler true classes=0x100000,1, num true = 2, num sampled = 2, unique = False, range max = 2, seed = 2, seed2 = 2 Patches ...

9.1CVSS7AI score0.0041EPSS
SaveExploits1References8
CVE
CVE
•added 2026/07/10 7:13 a.m.•66 views

CVE-2026-40008

The Apache IoTDB data management system (versions 1.0.0 before 2.0.10 ) is vulnerable to Unsafe Reflection (CWE-470 ) in its pipe processor. The component fails to validate or allowlist a fully qualified Java class name received from a Pipe Transfer RPC request, subsequently instantiating it usin...

9.8CVSS5.8AI score0.00597EPSS
SaveExploits0References2
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