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. Dependency Scanning using SBOM also detects vulnerabilities from proprietary advisories that this site does not include. Learn more about Dependency Scanning using SBOM →