TensorFlow vulnerable to `CHECK` fail in `LRNGrad`

ImpactIf LRNGrad is given an outputimage input tensor that is not 4-D, it results in a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfdepthradius = 1bias = 1.59018219alpha = 0.117728651beta = 0.404427052inputgrads = tf.random.uniformshape=4, 4, 4, 4...