Vulnerability · Published Feb 4, 2022 · Assigned by GitHub_M
CVE-2022-23591Stack overflow in Tensorflow
High 7.5
In plain English
A high-severity uncontrolled resource consumption 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 0.8% (higher than 57% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official description
Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Affected packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | tensorflow | 2.5.3 | GHSA-247x-2f9f-5wp7 |
| PyPI | tensorflow | 2.6.3 | GHSA-247x-2f9f-5wp7 |
| PyPI | tensorflow | 2.7.1 | GHSA-247x-2f9f-5wp7 |
| PyPI | tensorflow | 2.5.3, 2.6.3, 2.7.1 | PYSEC-2026-3084 |
| PyPI | tensorflow-cpu | 2.6.3 | GHSA-247x-2f9f-5wp7 |
| PyPI | tensorflow-cpu | 2.7.1 | GHSA-247x-2f9f-5wp7 |
| PyPI | tensorflow-cpu | 2.5.3, 2.6.3 | PYSEC-2022-100 |
| PyPI | tensorflow-cpu | 2.5.3 | GHSA-247x-2f9f-5wp7 |
| PyPI | tensorflow-gpu | 2.7.1 | GHSA-247x-2f9f-5wp7 |
| PyPI | tensorflow-gpu | 2.5.3, 2.6.3 | PYSEC-2022-155 |
| PyPI | tensorflow-gpu | 2.5.3 | GHSA-247x-2f9f-5wp7 |
| PyPI | tensorflow-gpu | 2.6.3 | GHSA-247x-2f9f-5wp7 |
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| tensorflow | tensorflow | >= 2.7.0, < 2.7.1>= 2.6.0, < 2.6.3< 2.5.3 |
Weakness: CWE-400 · Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H