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CVE-2022-23567

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Advisory Summaries

github_osv/GHSA-rrx2-r989-2c43

Integer overflows in Tensorflow ### Impact The implementations of `Sparse*Cwise*` ops https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service): ```python import tensorflow as tf import numpy as np tf.raw_ops.SparseDenseCwiseDiv( sp_indices=np.array([[9]]), sp_values=np.array([5]), sp_shape=np.array([92233720368., 92233720368]), dense=np.array([4])) ``` We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The latter is an instance of TFSA-2021-198 https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md (CVE-2021-41197) and is easily fixed by replacing a call to `TensorShape` constructor with a call to `BuildTensorShape` static helper factory. ### Patches We have patched the issue in GitHub commits 1b54cadd19391b60b6fcccd8d076426f7221d5e8 https://github.com/tensorflow/tensorflow/commit/1b54cadd19391b60b6fcccd8d076426f7221d5e8 and e952a89b7026b98fe8cbe626514a93ed68b7c510 https://github.com/tensorflow/tensorflow/commit/e952a89b7026b98fe8cbe626514a93ed68b7c510. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Faysal Hossain Shezan from University of Virginia.

gitlab/pypi/tensorflow-cpu/CVE-2022-23567

Integer overflows in Tensorflow The implementations of `Sparse*Cwise*` ops https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service): ```python import tensorflow as tf import numpy as np tf.raw_ops.SparseDenseCwiseDiv( sp_indices=np.array([[9]]), sp_values=np.array([5]), sp_shape=np.array([92233720368., 92233720368]), dense=np.array([4])) ``` We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The latter is an instance of TFSA-2021-198 https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md (CVE-2021-41197) and is easily fixed by replacing a call to `TensorShape` constructor with a call to `BuildTensorShape` static helper factory.

gitlab/pypi/tensorflow-gpu/CVE-2022-23567

Integer overflows in Tensorflow The implementations of `Sparse*Cwise*` ops https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service): ```python import tensorflow as tf import numpy as np tf.raw_ops.SparseDenseCwiseDiv( sp_indices=np.array([[9]]), sp_values=np.array([5]), sp_shape=np.array([92233720368., 92233720368]), dense=np.array([4])) ``` We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The latter is an instance of TFSA-2021-198 https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md (CVE-2021-41197) and is easily fixed by replacing a call to `TensorShape` constructor with a call to `BuildTensorShape` static helper factory.

pypa/tensorflow-cpu/PYSEC-2022-76

Tensorflow is an Open Source Machine Learning Framework. The implementations of `Sparse*Cwise*` ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

pypa/tensorflow-gpu/PYSEC-2022-131

Tensorflow is an Open Source Machine Learning Framework. The implementations of `Sparse*Cwise*` ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

pysec/PYSEC-2022-131

Tensorflow is an Open Source Machine Learning Framework. The implementations of `Sparse*Cwise*` ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

pysec/PYSEC-2022-76

Tensorflow is an Open Source Machine Learning Framework. The implementations of `Sparse*Cwise*` ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.