Vulnerability · Published Nov 18, 2022 · Assigned by GitHub_M
CVE-2022-41897`FractionalMaxPoolGrad` Heap out of bounds read in Tensorflow
Medium 4.8
In plain English
A medium-severity out-of-bounds read in tensorflow from tensorflow. Proof-of-concept exploit code is public. The chance it is exploited in the next 30 days is estimated at 0.5% (higher than 43% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official description
TensorFlow is an open source platform for machine learning. If `FractionMaxPoolGrad` is given outsize inputs `row_pooling_sequence` and `col_pooling_sequence`, TensorFlow will crash. We have patched the issue in GitHub commit d71090c3e5ca325bdf4b02eb236cfb3ee823e927. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Affected packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | tensorflow | 2.9.3 | GHSA-f2w8-jw48-fr7j |
| PyPI | tensorflow | 2.10.1, 2.8.4, 2.9.3 | PYSEC-2026-3165 |
| PyPI | tensorflow | 2.10.1 | GHSA-f2w8-jw48-fr7j |
| PyPI | tensorflow | 2.8.4 | GHSA-f2w8-jw48-fr7j |
| PyPI | tensorflow-cpu | 2.10.1 | GHSA-f2w8-jw48-fr7j |
| PyPI | tensorflow-cpu | 2.10.1, 2.8.4, 2.9.3 | PYSEC-2026-3313 |
| PyPI | tensorflow-cpu | 2.9.3 | GHSA-f2w8-jw48-fr7j |
| PyPI | tensorflow-cpu | 2.8.4 | GHSA-f2w8-jw48-fr7j |
| PyPI | tensorflow-gpu | 2.10.1, 2.8.4, 2.9.3 | PYSEC-2026-984 |
| PyPI | tensorflow-gpu | 2.8.4 | GHSA-f2w8-jw48-fr7j |
| PyPI | tensorflow-gpu | 2.9.3 | GHSA-f2w8-jw48-fr7j |
| PyPI | tensorflow-gpu | 2.10.1 | GHSA-f2w8-jw48-fr7j |
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| tensorflow | tensorflow | >= 2.10.0, < 2.10.1>= 2.9.0, < 2.9.3< 2.8.4 |
Weakness: CWE-125 · Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H