Advisory Package Curation

TensorFlow vulnerable to `CHECK` fail in `SetSize` ### Impact When `SetSize` receives an input `set_shape` that is not a 1D tensor, it gives a `CHECK` fails that can be used to trigger a denial of service attack. ```python import tensorflow as tf arg_0=1 arg_1=[1,1] arg_2=1 arg_3=True arg_4='' tf.raw_ops.SetSize(set_indices=arg_0, set_values=arg_1, set_shape=arg_2, validate_indices=arg_3, name=arg_4) ``` ### Patches We have patched the issue in GitHub commit cf70b79d2662c0d3c6af74583641e345fc939467 https://github.com/tensorflow/tensorflow/commit/cf70b79d2662c0d3c6af74583641e345fc939467. 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 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.

Reachable Assertion TensorFlow is an open source platform for machine learning. When `SetSize` receives an input `set_shape` that is not a 1D tensor, it gives a `CHECK` fails that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit cf70b79d2662c0d3c6af74583641e345fc939467. 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` fail in `SetSize` ### Impact When `SetSize` receives an input `set_shape` that is not a 1D tensor, it gives a `CHECK` fails that can be used to trigger a denial of service attack. ```python import tensorflow as tf arg_0=1 arg_1=[1,1] arg_2=1 arg_3=True arg_4='' tf.raw_ops.SetSize(set_indices=arg_0, set_values=arg_1, set_shape=arg_2, validate_indices=arg_3, name=arg_4) ``` ### Patches We have patched the issue in GitHub commit cf70b79d2662c0d3c6af74583641e345fc939467 https://github.com/tensorflow/tensorflow/commit/cf70b79d2662c0d3c6af74583641e345fc939467. 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 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.

TensorFlow vulnerable to `CHECK` fail in `SetSize` ### Impact When `SetSize` receives an input `set_shape` that is not a 1D tensor, it gives a `CHECK` fails that can be used to trigger a denial of service attack. ```python import tensorflow as tf arg_0=1 arg_1=[1,1] arg_2=1 arg_3=True arg_4='' tf.raw_ops.SetSize(set_indices=arg_0, set_values=arg_1, set_shape=arg_2, validate_indices=arg_3, name=arg_4) ``` ### Patches We have patched the issue in GitHub commit cf70b79d2662c0d3c6af74583641e345fc939467 https://github.com/tensorflow/tensorflow/commit/cf70b79d2662c0d3c6af74583641e345fc939467. 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 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.