CVE-2022-41893 `CHECK_EQ` fail in `tf.raw_ops.TensorListResize` in Tensorflow
Attackers can cause a denial of service in TensorFlow by passing nonscalar values to TensorListResize, triggering a CHECK failure.
- 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-2022-41893?
CVE-2022-41893 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. If `tf.raw_ops.TensorListResize` is given a nonscalar value for input `size`, it results `CHECK` fail which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 888e34b49009a4e734c27ab0c43b0b5102682c56. 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-617
Which versions are affected by CVE-2022-41893?
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-2022-41893?
Upgrade tensorflow to a fixed version for your release line: 2.8.4, 2.9.3 or 2.10.1.
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-2022-41893 being exploited?
It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-41893 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-11531, BIT-tensorflow-2022-41893, GHSA-67pf-62xr-q35m, PYSEC-2026-3118, PYSEC-2026-3284, PYSEC-2026-958.