PT-2026-59888

Impact If QuantizedAvgPool is given min input or max input 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 ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "SAME" input = tf.constant1, shape=1,4,4,2,...

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...

PT-2026-59928

Impact nn ops.fractional avg pool v2 and nn ops.fractional max pool v2 require the first and fourth elements of their parameter pooling ratio to be equal to 1.0, as pooling on batch and channel dimensions is not supported. python import tensorflow as tf import os import numpy as np from...

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...

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...

PT-2026-59997

Impact An input pooling ratio that is smaller than 1 will trigger a heap OOB in tf.raw ops.FractionalMaxPool and tf.raw ops.FractionalAvgPool. Patches We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also...

PT-2026-59722

Impact If QuantizedAvgPool is given min input or max input 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 ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "SAME" input = tf.constant1, shape=1,4,4,2,...

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,...

PT-2026-59832

Impact The AvgPoolOp function takes an argument ksize that must be positive but is not checked. A negative ksize can trigger a CHECK failure and crash the program. python import tensorflow as tf import numpy as np value = np.ones1, 1, 1, 1 ksize = 1, 1e20, 1, 1 strides = 1, 1, 1, 1 padding = 'SAM...

PT-2026-59750

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...

PT-2026-59782

Impact If FractionMaxPoolGrad is given outsize inputs row pooling sequence and col pooling sequence, TensorFlow will crash. python import tensorflow as tf tf.raw ops.FractionMaxPoolGrad orig input = 1, 1, 1, 1, 1, orig output = 1, 1, 1, out backprop = 3, 3, 6, row pooling sequence = -0x4000000, 1...

PT-2026-59927

Impact If FractionMaxPoolGrad is given outsize inputs row pooling sequence and col pooling sequence, TensorFlow will crash. python import tensorflow as tf tf.raw ops.FractionMaxPoolGrad orig input = 1, 1, 1, 1, 1, orig output = 1, 1, 1, out backprop = 3, 3, 6, row pooling sequence = -0x4000000, 1...

PT-2026-59876

Impact An input pooling ratio that is smaller than 1 will trigger a heap OOB in tf.raw ops.FractionalMaxPool and tf.raw ops.FractionalAvgPool. Patches We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also...

PT-2026-59740

Impact python import os os.environ'TF ENABLE ONEDNN OPTS' = '0' import tensorflow as tf printtf. version with tf.device"CPU": ksize = 1, 40, 128, 1 strides = 1, 128, 128, 30 padding = "SAME" data format = "NHWC" orig input shape = 11, 9, 78, 9 grad = tf.saturate casttf.random.uniform16, 16, 16, 1...

SUSE CVE-2026-11564

libcurl keeps previously used connections in a connection pool for subsequent transfers to reuse if one of them matches the setup. An easy handle that first uses default native CA trust can continue trusting the native platform store after the application switches that same handle to custom CA...

PYSEC-2026-3134 Division by zero in Tensorflow

Impact The implementation of FractionalMaxPool can be made to crash a TensorFlow process via a division by 0: python import tensorflow as tf import numpy as np tf.rawops.FractionalMaxPool value=tf.constantvalue=1, 4, 2, 3, dtype=tf.int64, poolingratio=1.0, 1.44, 1.73, 1.0, pseudorandom=False,...

Division by zero in Tensorflow

Impact The implementation of FractionalMaxPool can be made to crash a TensorFlow process via a division by 0:pythonimport tensorflow as tfimport numpy as nptf.rawops.FractionalMaxPool value=tf.constantvalue=1, 4, 2, 3, dtype=tf.int64, poolingratio=1.0, 1.44, 1.73, 1.0, pseudorandom=False,...

Memory exhaustion in Tensorflow

Impact The implementation of ThreadPoolHandle can be used to trigger a denial of service attack by allocating too much memory:pythonimport tensorflow as tfy = tf.rawops.ThreadPoolHandlenumthreads=0x60000000,displayname='tf'This is because the numthreads argument is only checked to not be negative...

Division by zero in Tensorflow

Impact The estimator for the cost of some convolution operations can be made to execute a division by 0:pythonimport tensorflow as [email protected] test: y=tf.rawops.AvgPoolGrad originputshape=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, padding='VALID',...

Null pointer dereference in TensorFlow

Impact The implementation of QuantizedMaxPool has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer.pythonimport tensorflow as tftf.rawops.QuantizedMaxPool input = tf.constant4, dtype=tf.quint8, mininput = , maxinput = 1, ksize = 1, 1, 1, 1, stride...