CVE-2022-35973

Severity CVSS v4.0:

Pending analysis

Type:

Unavailable / Other

Publication date:

16/09/2022

Last modified:

20/09/2022

Description

TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. 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.

Impact

Vector 3.x

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H CVSS v3.1 Severity and Metrics:

Base Score: 7.50 HIGH
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Attack Vector (AV): Network
Attack Complexity (AC): Low
Privileges Required (PR): None
User Interaction (UI): None
Scope (S): Unchanged
Confidentiality (C): None
Integrity (I): None
Availability (A): High

Base Score 3.x

7.50

Severity 3.x

HIGH

Vulnerable products and versions

CPE	From	Up to
cpe:2.3:a:google:tensorflow::::::::	2.7.0 (including)	2.7.2 (excluding)
cpe:2.3:a:google:tensorflow::::::::	2.8.0 (including)	2.8.1 (excluding)
cpe:2.3:a:google:tensorflow::::::::	2.9.0 (including)	2.9.1 (excluding)
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::::::

To consult the complete list of CPE names with products and versions, see this page

CVE-2022-35973

Description

Impact

Vulnerable products and versions

References to Advisories, Solutions, and Tools