CVE-2022-29199: 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.LoadAndRemapMatrix 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 assumes
initializing_values` is a vector but there is no validation for this before accessing its value. 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-p9rc-rmr5-529j
- github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/load_and_remap_matrix_op.cc
- github.com/tensorflow/tensorflow/commit/3150642acbbe254e3c3c5d2232143fa591855ac9
- 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-p9rc-rmr5-529j
- nvd.nist.gov/vuln/detail/CVE-2022-29199
Detect and mitigate CVE-2022-29199 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 →