CVE-2022-35973 - CVE House

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Status published Medium CVE-2022-35973

Segfault in `QuantizedMatMul` in TensorFlow

5.9 CVSS

Vulnerability 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 Analysis

Refer to official advisory for detailed impact metrics.

Remediation

Ensure systems are updated to the latest vendor-supplied patch levels.

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Credits & Attribution

No credits recorded in the NVD database.

References

More from tensorflow

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TensorFlow segfault in array_ops.upper_bound

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TensorFlow has double free in Fractional(Max/Avg)Pool

TensorFlow has null dereference on ParallelConcat with XLA

Affected Vendor

tensorflow

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Affected Software

tensorflow

Vulnerable Versions:

< 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1

Timeline

Official Publish: September 16th, 2022

Last Modified: April 23rd, 2025

Added to House: July 21st, 2026

CVSS Vectors

V3: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

Weaknesses (CWE)

MITRE ATT&CK TTPs

T1190 Exploit Public-Facing Application

T1059 Command and Scripting Interpreter

T1068 Exploitation for Privilege Escalation

Privilege Escalation

T1213 Data from Information Repositories

T1565.002 Stored Data Manipulation