MEDIUM · 5.9

CVE-2022-35986

TensorFlow is an open source platform for machine learning. If `RaggedBincount` is given an empty input tensor `splits`, it results in a segfault that can be used to trigger a denial of service attack...

Vulnerability Description

TensorFlow is an open source platform for machine learning. If `RaggedBincount` is given an empty input tensor `splits`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7a4591fd4f065f4fa903593bc39b2f79530a74b8. 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< 2.7.2

Related Weaknesses (CWE)

References

FAQ

What is CVE-2022-35986?

CVE-2022-35986 is a vulnerability with a CVSS score of 5.9 (MEDIUM). TensorFlow is an open source platform for machine learning. If `RaggedBincount` is given an empty input tensor `splits`, it results in a segfault that can be used to trigger a denial of service attack...

How severe is CVE-2022-35986?

CVE-2022-35986 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-2022-35986?

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