Vulnerability · Published Sep 16, 2022 · Assigned by GitHub_M
CVE-2022-35990`CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient` in TensorFlow
Medium 5.9
In plain English
A medium-severity security flaw in tensorflow from tensorflow. There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.5% (higher than 40% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official description
TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient` receives input `min` or `max` of rank other than 1, 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 packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | tensorflow | 2.9.1 | GHSA-h7ff-cfc9-wmmh |
| PyPI | tensorflow | 2.8.1 | GHSA-h7ff-cfc9-wmmh |
| PyPI | tensorflow | 2.7.2 | GHSA-h7ff-cfc9-wmmh |
| PyPI | tensorflow | 2.7.2, 2.8.1, 2.9.1 | PYSEC-2026-3199 |
| PyPI | tensorflow-cpu | 2.7.2, 2.8.1, 2.9.1 | PYSEC-2026-3338 |
| PyPI | tensorflow-cpu | 2.7.2 | GHSA-h7ff-cfc9-wmmh |
| PyPI | tensorflow-cpu | 2.8.1 | GHSA-h7ff-cfc9-wmmh |
| PyPI | tensorflow-cpu | 2.9.1 | GHSA-h7ff-cfc9-wmmh |
| PyPI | tensorflow-gpu | 2.9.1 | GHSA-h7ff-cfc9-wmmh |
| PyPI | tensorflow-gpu | 2.7.2, 2.8.1, 2.9.1 | PYSEC-2026-1006 |
| PyPI | tensorflow-gpu | 2.8.1 | GHSA-h7ff-cfc9-wmmh |
| PyPI | tensorflow-gpu | 2.7.2 | GHSA-h7ff-cfc9-wmmh |
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| tensorflow | tensorflow | < 2.7.2>= 2.8.0, < 2.8.1>= 2.9.0, < 2.9.1 |
Weakness: CWE-617 · Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H