Vulnerability · Published Nov 5, 2021 · Assigned by GitHub_M
CVE-2021-41225A use of uninitialized value vulnerability in Tensorflow
Medium 5.5
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 0.2% (higher than 9% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official description
TensorFlow is an open source platform for machine learning. In affected versions TensorFlow's Grappler optimizer has a use of unitialized variable. If the `train_nodes` vector (obtained from the saved model that gets optimized) does not contain a `Dequeue` node, then `dequeue_node` is left unitialized. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Affected packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | tensorflow | 2.4.4, 2.5.2, 2.6.1, 2.7.0 | PYSEC-2021-417 |
| PyPI | tensorflow | 2.6.1 | GHSA-7r94-xv9v-63jw |
| PyPI | tensorflow | 2.5.2 | GHSA-7r94-xv9v-63jw |
| PyPI | tensorflow | 2.4.4 | GHSA-7r94-xv9v-63jw |
| PyPI | tensorflow-cpu | 2.5.2 | GHSA-7r94-xv9v-63jw |
| PyPI | tensorflow-cpu | 2.4.4, 2.5.2, 2.6.1, 2.7.0 | PYSEC-2021-634 |
| PyPI | tensorflow-cpu | 2.6.1 | GHSA-7r94-xv9v-63jw |
| PyPI | tensorflow-cpu | 2.4.4 | GHSA-7r94-xv9v-63jw |
| PyPI | tensorflow-gpu | 2.4.4, 2.5.2, 2.6.1, 2.7.0 | PYSEC-2021-832 |
| PyPI | tensorflow-gpu | 2.6.1 | GHSA-7r94-xv9v-63jw |
| PyPI | tensorflow-gpu | 2.5.2 | GHSA-7r94-xv9v-63jw |
| PyPI | tensorflow-gpu | 2.4.4 | GHSA-7r94-xv9v-63jw |
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| tensorflow | tensorflow | >= 2.6.0, < 2.6.1>= 2.5.0, < 2.5.2< 2.4.4 |
Weakness: CWE-908 · Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H