CVE-2022-35982: Segfault in `SparseBincount` in TensorFlow

Published Sep 16, 2022
·
Updated

TensorFlow is an open source platform for machine learning. If SparseBincount is given inputs for indices, values, and denseshape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. 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.

Affected Software

7 affected components
Google TensorFlow<2.7.2
Google TensorFlow>=2.8.0<2.8.1
Google TensorFlow>=2.9.0<2.9.1
Google TensorFlow=2.10-rc0
Google TensorFlow=2.10-rc1
Google TensorFlow=2.10-rc2
Google TensorFlow=2.10-rc3

Event History

Sep 16, 2022
CVE Published
via MITRE·09:30 PM
Data Sourced
via MITRE·09:30 PM
DescriptionSeverityWeakness

Frequently Asked Questions

1

What is the severity of CVE-2022-35982?

CVE-2022-35982 has a severity rating of high due to its potential for denial of service attacks.

2

How do I fix CVE-2022-35982?

To fix CVE-2022-35982, update TensorFlow to version 2.10-rc4 or later.

3

What product is affected by CVE-2022-35982?

CVE-2022-35982 affects Google TensorFlow versions prior to 2.10-rc4.

4

What type of vulnerability is CVE-2022-35982?

CVE-2022-35982 is a segmentation fault vulnerability that can trigger denial of service.

5

What are the conditions that trigger CVE-2022-35982?

CVE-2022-35982 is triggered when SparseBincount receives invalid inputs for indices, values, and dense_shape.

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