CVE-2022-29196: Improper Input Validation
(updated )
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.Conv3DBackpropFilterV2 does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. The code does not validate that the filter_sizes argument is a vector. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
References
- github.com/advisories/GHSA-5v77-j66x-4c4g
- github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/conv_grad_ops_3d.cc
- github.com/tensorflow/tensorflow/commit/174c5096f303d5be7ed2ca2662b08371bff4ab88
- github.com/tensorflow/tensorflow/releases/tag/v2.6.4
- github.com/tensorflow/tensorflow/releases/tag/v2.7.2
- github.com/tensorflow/tensorflow/releases/tag/v2.8.1
- github.com/tensorflow/tensorflow/releases/tag/v2.9.0
- github.com/tensorflow/tensorflow/security/advisories/GHSA-5v77-j66x-4c4g
- nvd.nist.gov/vuln/detail/CVE-2022-29196
Code Behaviors & Features
Detect and mitigate CVE-2022-29196 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 →