GHSA-pgcq-h79j-2f69 Incomplete validation of shapes in multiple TF ops

• PyPI tensorflow: >= 2.6.0, < 2.6.1 → fixed in 2.6.1 • PyPI tensorflow: >= 2.5.0, < 2.5.2 → fixed in 2.5.2 • PyPI tensorflow: < 2.4.4 → fixed in 2.4.4 • PyPI tensorflow-cpu: >= 2.6.0, < 2.6.1 → fixed in 2.6.1 • PyPI tensorflow-cpu: >= 2.5.0, < 2.5.2 → fixed in 2.5.2 • PyPI tensorflow-cpu: < 2.4.4 → fixed in 2.4.4 • PyPI tensorflow-gpu: >= 2.6.0, < 2.6.1 → fixed in 2.6.1 • PyPI tensorflow-gpu: >= 2.5.0, < 2.5.2 → fixed in 2.5.2 • PyPI tensorflow-gpu: < 2.4.4 → fixed in 2.4.4

Impact Several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues. Patches We have patched the issue in GitHub commits 68422b215e618df5ad375bcdc6d2052e9fd3080a, 4d74d8a00b07441cba090a02e0dd9ed385145bf4, 579261dcd446385831fe4f7457d802a59685121d, da4aad5946be30e5f049920fa076e1f7ef021261, 4dddb2fd0b01cdd196101afbba6518658a2c9e07, and e7f497570abb6b4ae5af4970620cd880e4c0c904. These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.