CVE-2022-35973

Segfault in `QuantizedMatMul` in TensorFlow

HIGH

7.5

CVSS Score

Published: September 16, 2022 at 09:00 PM UTC

Updated: June 17, 2026 at 04:52 AM UTC

2 products affected across 2 vendorsTensorflowTensorFlow

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Severity

HIGH7.5

Exploit prediction

EPSS 0.5%

SSVC

No known exploit

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.

Affected

Our own answer: ranges merged, affected separated from platform-only, with confidence and review flags.

Tensorflow · Google

95%

2.7.0 ≤ v < 2.7.22.8.0 ≤ v < 2.8.12.9.0 ≤ v < 2.9.12.10 rc0 2.10 rc1 2.10 rc2 2.10 rc3

Affected range stops below 2.7.2, so it looks safe — our inference, not a vendor statement

Affected range stops below 2.8.1, so it looks safe — our inference, not a vendor statement

Affected range stops below 2.9.1, so it looks safe — our inference, not a vendor statement

TensorFlow · Tensorflow

60%

v < 2.7.2v < 2.8.1v < 2.9.1

Affected range stops below 2.7.2, so it looks safe — our inference, not a vendor statement

Affected range stops below 2.8.1, so it looks safe — our inference, not a vendor statement

Affected range stops below 2.9.1, so it looks safe — our inference, not a vendor statement

Remediation

No guide yet

No remediation guidance has been written for this CVE yet. What the record does show:

Patch and advisory references

References (2)

x_refsource_MISCPatchThird Party Advisory

Source: [email protected]

https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48

x_refsource_CONFIRMPatchThird Party Advisory

Source: [email protected]

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v

SSVC — Action Prioritization

SSVCNo known exploitNot automatablePartial impact

SSVC signals action urgency (what to patch first), separate from CVSS which measures severity.

CVSS

7.5HIGH[email protected]

Attack Vector: NETWORK
Complexity: LOW
Privileges: NONE
User Interaction: NONE
Scope: UNCHANGED
Confidentiality: NONE
Integrity: NONE
Availability: HIGH

Vector?

Quick Info

StatusMODIFIED

CWE

CWE-20NVD-CWE-noinfo

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