PT-2021-18331 · Google · Tensorflow
Yakun Zhang
+1
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Published
2021-05-14
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Updated
2024-03-06
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CVE-2021-29580
CVSS v3.1
5.5
Medium
| Vector | AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
Name of the Vulnerable Software and Affected Versions
TensorFlow versions prior to 2.5.0
TensorFlow version 2.4.2
TensorFlow version 2.3.3
TensorFlow version 2.2.3
TensorFlow version 2.1.4
Description
The implementation of
tf.raw ops.FractionalMaxPoolGrad triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a CHECK condition becomes false and aborts the process. The implementation fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues.Recommendations
For versions prior to 2.5.0, update to TensorFlow 2.5.0 or later.
For version 2.4.2, cherrypick the commit to fix the issue.
For version 2.3.3, cherrypick the commit to fix the issue.
For version 2.2.3, cherrypick the commit to fix the issue.
For version 2.1.4, cherrypick the commit to fix the issue.
As a temporary workaround, consider disabling the
tf.raw ops.FractionalMaxPoolGrad function until a patch is available.Exploit
Fix
Use of Uninitialized Resource
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Weakness Enumeration
Related Identifiers
Affected Products
Tensorflow