Advisory Package Curation

TensorFlow vulnerable to `CHECK` failure in tf.reshape via overflows ### Impact The implementation of tf.reshape op in TensorFlow is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by overflowing the number of elements in a tensor: ```python import tensorflow as tf tf.reshape(tensor=[[1]],shape=tf.constant([0 for i in range(255)], dtype=tf.int64)) ``` This is another instance of TFSA-2021-198 https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md (https://github.com/advisories/GHSA-prcg-wp5q-rv7p) ### Patches We have patched the issue in GitHub commit 61f0f9b94df8c0411f0ad0ecc2fec2d3f3c33555 https://github.com/tensorflow/tensorflow/commit/61f0f9b94df8c0411f0ad0ecc2fec2d3f3c33555. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. ### For more information Please consult our security guide https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Kang Hong Jin from Singapore Management University.

TensorFlow vulnerable to `CHECK` failure in tf.reshape via overflows TensorFlow is an open source platform for machine learning. The implementation of tf.reshape op in TensorFlow is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by overflowing the number of elements in a tensor. This issue has been patched in GitHub commit 61f0f9b94df8c0411f0ad0ecc2fec2d3f3c33555. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow vulnerable to `CHECK` failure in tf.reshape via overflows ### Impact The implementation of tf.reshape op in TensorFlow is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by overflowing the number of elements in a tensor: ```python import tensorflow as tf tf.reshape(tensor=[[1]],shape=tf.constant([0 for i in range(255)], dtype=tf.int64)) ``` This is another instance of TFSA-2021-198 https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md (https://github.com/advisories/GHSA-prcg-wp5q-rv7p) ### Patches We have patched the issue in GitHub commit 61f0f9b94df8c0411f0ad0ecc2fec2d3f3c33555 https://github.com/tensorflow/tensorflow/commit/61f0f9b94df8c0411f0ad0ecc2fec2d3f3c33555. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. ### For more information Please consult our security guide https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Kang Hong Jin from Singapore Management University.

TensorFlow vulnerable to `CHECK` failure in tf.reshape via overflows ### Impact The implementation of tf.reshape op in TensorFlow is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by overflowing the number of elements in a tensor: ```python import tensorflow as tf tf.reshape(tensor=[[1]],shape=tf.constant([0 for i in range(255)], dtype=tf.int64)) ``` This is another instance of TFSA-2021-198 https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md (https://github.com/advisories/GHSA-prcg-wp5q-rv7p) ### Patches We have patched the issue in GitHub commit 61f0f9b94df8c0411f0ad0ecc2fec2d3f3c33555 https://github.com/tensorflow/tensorflow/commit/61f0f9b94df8c0411f0ad0ecc2fec2d3f3c33555. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. ### For more information Please consult our security guide https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Kang Hong Jin from Singapore Management University.