CVE-2022-41900 FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow
Attackers can trigger heap out-of-bounds access in FractionalMaxPool and FractionalAVGPool, leading to crashes or remote code execution.
- Exploited in the wild
- Not known
- Login needed
- Any signed-in user
- Attackable
- Over the internet
- Victim action needed
- A user has to click or open something
- Fix
- Available
What is CVE-2022-41900?
CVE-2022-41900 is a high-severity memory corruption vulnerability in Google Tensorflow, published on 18 Nov 2022. Any signed-in user can exploit it over the network, and only if a user opens a file or follows a link.
Official description
TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.
Which versions are affected by CVE-2022-41900?
22 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.
| Package | Affected | Fixed in |
|---|---|---|
tensorflow Bitnami | All versions | 2.8.4, 2.9.3, 2.10.1 |
tensorflow PyPI | All versions | 2.8.4, 2.9.3, 2.10.1 |
tensorflow PyPI | All versions | 2.8.4 |
tensorflow PyPI | All versions | 2.8.4 |
tensorflow PyPI | From 2.10.0 | 2.10.1 |
tensorflow PyPI | From 2.10.0 | 2.10.1 |
16 more packages
tensorflow PyPI | From 2.9.0 | 2.9.3 |
tensorflow PyPI | From 2.9.0 | 2.9.3 |
tensorflow-cpu PyPI | All versions | 2.8.4, 2.9.3, 2.10.1 |
tensorflow-cpu PyPI | All versions | 2.8.4 |
tensorflow-cpu PyPI | All versions | 2.8.4 |
tensorflow-cpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-cpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-cpu PyPI | From 2.9.0 | 2.9.3 |
tensorflow-cpu PyPI | From 2.9.0 | 2.9.3 |
tensorflow-gpu PyPI | All versions | 2.8.4, 2.9.3, 2.10.1 |
tensorflow-gpu PyPI | All versions | 2.8.4 |
tensorflow-gpu PyPI | All versions | 2.8.4 |
tensorflow-gpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-gpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-gpu PyPI | From 2.9.0 | 2.9.3 |
tensorflow-gpu PyPI | From 2.9.0 | 2.9.3 |
Products include Google Tensorflow.
How do I fix CVE-2022-41900?
Upgrade tensorflow to a fixed version for your release line: 2.8.4, 2.9.3 or 2.10.1.
Upgrade to the fixed version. Memory-safe languages, compiler hardening and fuzzing prevent most new cases. More about Memory corruption.
Is CVE-2022-41900 being exploited?
It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-41900 exists.
Other vulnerabilities in Google Tensorflow
- CVE-2023-25668 TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation
- CVE-2018-7575 Integer Overflow or Wraparound in Google TensorFlow
- CVE-2021-37678 Arbitrary code execution due to YAML deserialization
- CVE-2021-35958 Path traversal in n/a
- CVE-2020-15202 Integer truncation in Shard API usage
Sources
Also known as AZL-11539, BIT-tensorflow-2022-41900, GHSA-xvwp-h6jv-7472, PYSEC-2026-1049, PYSEC-2026-3261, PYSEC-2026-3383.