CVE-2022-21728: Out-of-bounds Read
(updated )
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for ReverseSequence
does not fully validate the value of batch_dim
and can result in a heap OOB read. There is a check to make sure the value of batch_dim
does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python’s negative indexing , however if the value is too negative then the implementation of Dim
would access elements before the start of an array. 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.
References
- github.com/advisories/GHSA-6gmv-pjp9-p8w8
- github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h
- github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc
- github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995
- github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8
- nvd.nist.gov/vuln/detail/CVE-2022-21728
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