What’s Vulnerable › Vulnerabilities

CVE-2022-35974: Segfault in `QuantizeDownAndShrinkRange` 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-20

Description

TensorFlow is an open source platform for machine learning. If `QuantizeDownAndShrinkRange` is given nonscalar inputs for `input_min` or `input_max`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. 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: from 2.7.0 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/73ad1815ebcfeb7c051f9c2f7ab5024380ca8613
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vgvh-2pf4-jr2x
• https://github.com/tensorflow/tensorflow/commit/73ad1815ebcfeb7c051f9c2f7ab5024380ca8613
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vgvh-2pf4-jr2x

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