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CVE-2022-35996: Floating point exception in `Conv2D` in TensorFlow

• Severity: high (CVSS 7.5 v3.1)
• Exploited in the wild: not listed in CISA KEV
• EPSS: 0.5% probability of exploitation in the next 30 days
• Public exploit or detection template: none known
• Published: 2022-09-16 · updated 2026-06-17
• Weakness: CWE-369

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.

Affected products

• tensorflow: before 2.7.2; from 2.8.0 before 2.8.1; from 2.9.0 before 2.9.1; 2.10-rc0, 2.10-rc1, 2.10-rc2, 2.10-rc3 — fixed in 2.7.2, 2.8.1, 2.9.1

How to fix

Upgrade to a fixed version: tensorflow 2.7.2, 2.8.1, 2.9.1. Check the vendor advisory for mitigations.

References

• https://github.com/tensorflow/tensorflow/commit/611d80db29dd7b0cfb755772c69d60ae5bca05f9
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q5jv-m6qw-5g37
• https://github.com/tensorflow/tensorflow/commit/611d80db29dd7b0cfb755772c69d60ae5bca05f9
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q5jv-m6qw-5g37

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