PT-2021-21767 · Google · Tensorflow
Published
2021-08-12
·
Updated
2024-03-06
·
CVE-2021-37651
CVSS v4.0
8.4
High
| Vector | AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N |
Name of the Vulnerable Software and Affected Versions
TensorFlow versions prior to 2.6.0
TensorFlow version 2.5.1
TensorFlow version 2.4.3
TensorFlow version 2.3.4
Description
The implementation for
tf.raw ops.FractionalAvgPoolGrad can be tricked into accessing data outside of bounds of heap allocated buffers. The issue arises because the implementation does not validate that the input tensor is non-empty, resulting in the construction of an empty EigenDoubleMatrixMap and subsequent access to this buffer with indices that are outside of the empty area.Recommendations
For TensorFlow versions prior to 2.6.0, update to version 2.6.0 or later.
For TensorFlow version 2.5.1, apply the patch from GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30.
For TensorFlow version 2.4.3, apply the patch from GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30.
For TensorFlow version 2.3.4, apply the patch from GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30.
As a temporary workaround, consider restricting the use of the
tf.raw ops.FractionalAvgPoolGrad function until a patch is available.Fix
Out of bounds Read
Memory Corruption
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Related Identifiers
Affected Products
Tensorflow