CVE-2022-41883 Out of bounds segmentation fault due to unequal op inputs in Tensorflow
An attacker can cause a segmentation fault and crash the application by providing unequal input sizes to TensorFlow operations.
- 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-2022-41883?
CVE-2022-41883 is a medium-severity denial of service 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. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. 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.
Weakness: CWE-125
Which versions are affected by CVE-2022-41883?
10 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.
| Package | Affected | Fixed in |
|---|---|---|
tensorflow Bitnami | From 2.10.0 | 2.10.1 |
tensorflow PyPI | From 2.10.0 | 2.10.1 |
tensorflow PyPI | From 2.10.0 | 2.10.1 |
tensorflow PyPI | From 2.10.0 | 2.10.1 |
tensorflow-cpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-cpu PyPI | From 2.10.0 | 2.10.1 |
4 more packages
tensorflow-cpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-gpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-gpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-gpu PyPI | From 2.10.0 | 2.10.1 |
Products include Google Tensorflow.
How do I fix CVE-2022-41883?
Upgrade tensorflow to 2.10.1 or later.
Upgrade, then put limits on request size, rate and nesting depth so one client cannot exhaust the service. More about Denial of service.
Is CVE-2022-41883 being exploited?
It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-41883 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 BIT-tensorflow-2022-41883, GHSA-w58w-79xv-6vcj, PYSEC-2026-1042, PYSEC-2026-3251, PYSEC-2026-3376.