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HIGH · 7.6

CVE-2022-21727

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the defa...

Vulnerability Description

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. 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.

CVSS Score

7.6

HIGH

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality
LOW
Integrity
LOW
Availability
HIGH

Affected Products

VendorProductVersions
GoogleTensorflow<= 2.5.2

Related Weaknesses (CWE)

CWE-190

References

FAQ

What is CVE-2022-21727?

CVE-2022-21727 is a vulnerability with a CVSS score of 7.6 (HIGH). Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the defa...

How severe is CVE-2022-21727?

CVE-2022-21727 has been rated HIGH with a CVSS base score of 7.6/10. Review the CVSS metrics above for detailed severity breakdown.

Is there a patch for CVE-2022-21727?

Check the references section above for vendor advisories and patch information. Affected products include: Google Tensorflow.