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VULNERABILITIES

CVE-2022-35970 Details

Description

TensorFlow is an open source platform for machine learning. If `QuantizedInstanceNorm` is given `x_min` or `x_max` 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 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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.

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References to Advisories, Solutions, and Tools

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Weakness Enumeration

CWE-IDCWE NameSource
NVD-CWE-noinfoInsufficient Information to Classify Weakness[email protected]
CWE-20Improper Input Validation[email protected]

Affected Products

ProductVersions
google tensorflow
>= 2.7.0, < 2.7.2
>= 2.8.0, < 2.8.1
>= 2.9.0, < 2.9.1
2.10 rc0
2.10 rc1

CPE

  • cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.10:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.10:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.10:rc2:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.10:rc3:*:*:*:*:*:*

Remediation

  • No remediation found in references.

Change History

5 change records found show changes


QUICK INFO

CVE Dictionary Entry:
CVE-2022-35970
NVD Published Date:
Sep 16, 2022
NVD Last Modified:
Jun 17, 2026
Source:
[email protected]
CVE-2022-35970 Details - Not Deferred