CVE-2022-35996 - CVE House
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Status published Medium CVE-2022-35996

Floating point exception in `Conv2D` in TensorFlow

Vulnerability Description

TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. 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

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Affected Vendor

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)

CWE-369

MITRE ATT&CK TTPs

T1203 Exploitation for Client Execution
Execution
T1499.003 Application Exhaustion Flood
Impact