TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
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Affected Vendors & Products
References
History
No history.
MITRE
Status: PUBLISHED
Assigner: GitHub_M
Published: 2021-08-12T21:00:19
Updated: 2024-08-04T01:23:01.436Z
Reserved: 2021-07-29T00:00:00
Link: CVE-2021-37651
Vulnrichment
No data.
NVD
Status : Modified
Published: 2021-08-12T21:15:08.170
Modified: 2024-11-21T06:15:36.860
Link: CVE-2021-37651
Redhat
No data.