PYSEC-2026-3083 TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. 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" dataformat = "NHWC"...

PYSEC-2026-3338 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

Impact When tf.quantization.fakequantwithminmaxvarsperchannelgradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None...

TensorFlow vulnerable to segfault in `BlockLSTMGradV2`

ImpactThe implementation of BlockLSTMGradV2 does not fully validate its inputs. - wci, wcf, wco, b must be rank 1 - w, csprev, hprev must be rank 2 - x must be rank 3This results in a a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfusepeephole =...

PYSEC-2026-3318 TensorFlow vulnerable to segfault in `BlockLSTMGradV2`

Impact The implementation of BlockLSTMGradV2 does not fully validate its inputs. - wci, wcf, wco, b must be rank 1 - w, csprev, hprev must be rank 2 - x must be rank 3 This results in a a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf usepeephole =...

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 ...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsGradient`

ImpactWhen tf.quantization.fakequantwithminmaxvarsgradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2,...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsGradient`

ImpactWhen tf.quantization.fakequantwithminmaxvarsgradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2,...

PYSEC-2026-3364 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsGradient`

Impact When tf.quantization.fakequantwithminmaxvarsgradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2, dtype=tf.float...

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...

When Cheap Gradients Fail: The Measurement Cost of Attacking Quantum Classifiers

Adversarial perturbations threaten machine learning classifiers, including variational quantum classifiers. We show that finite quantum measurement statistics shot noise act as a built-in defense against gradient-based test-time attacks whose cost scales unfavorably for the attacker. Because ever...

PT-2026-59818

Impact If SparseFillEmptyRowsGrad is given empty inputs, TensorFlow will crash. python import tensorflow as tf tf.raw ops.SparseFillEmptyRowsGrad reverse index map=, grad values=, name=None Patches We have patched the issue in GitHub commit af4a6a3c8b95022c351edae94560acc61253a1b8. The fix will b...

PT-2026-59917

Impact If LRNGrad is given an output image input tensor that is not 4-D, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf depth radius = 1 bias = 1.59018219 alpha = 0.117728651 beta = 0.404427052 input grads =...

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-2026-59702

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-2026-59740

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...

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...

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',...

PYSEC-2026-3247 Out of bounds read in Tensorflow

Impact The implementation of FractionalAvgPoolGrad does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap: python import tensorflow as tf @tf.function def test: y = tf.rawops.FractionalAvgPoolGrad originputtensorshape=2,2,2,2,...

Out of bounds read in Tensorflow

Impact The implementation of FractionalAvgPoolGrad does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap:pythonimport tensorflow as [email protected] test: y = tf.rawops.FractionalAvgPoolGrad originputtensorshape=2,2,2,2,...

Securing Autonomous Vehicle Systems Via Twin-Aware Federated Reinforcement Learning

Federated reinforcement learning FRL is crucial for enabling collaborative learning across multiple agents without sharing raw data, thereby enhancing privacy and scalability in the decision-making process within dynamic vehicular environments. However, poisoning attacks pose a significant threat...