MEDIUM · 5.9

CVE-2022-35966

TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a ...

Vulnerability Description

TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

CVSS Score

5.9

MEDIUM

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

Affected Products

VendorProductVersions
GoogleTensorflow>= 2.7.0, < 2.7.2

Related Weaknesses (CWE)

References

FAQ

What is CVE-2022-35966?

CVE-2022-35966 is a vulnerability with a CVSS score of 5.9 (MEDIUM). TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a ...

How severe is CVE-2022-35966?

CVE-2022-35966 has been rated MEDIUM with a CVSS base score of 5.9/10. Review the CVSS metrics above for detailed severity breakdown.

Is there a patch for CVE-2022-35966?

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