What’s Vulnerable › Vulnerabilities

CVE-2022-36005: `CHECK` fail in `FakeQuantWithMinMaxVarsGradient` 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-617

Description

TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_gradient` receives input `min` or `max` that is nonscalar, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. 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/f3cf67ac5705f4f04721d15e485e192bb319feed
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r26c-679w-mrjm
• https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feed
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r26c-679w-mrjm

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