CVE-2022-35960 `CHECK` failure in `TensorListReserve` in TensorFlow
An attacker can cause a denial of service in TensorFlow by providing a multi-element tensor to TensorListReserve, triggering a CHECK failure.
- Exploited in the wild
- Not known
- Login needed
- Not needed
- Attackable
- Over the internet
- Victim action needed
- Not needed
- Fix
- Available
What is CVE-2022-35960?
CVE-2022-35960 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 16 Sep 2022. An attacker can exploit it over the internet without logging in, with no action from the victim.
Official description
TensorFlow is an open source platform for machine learning. In `core/kernels/list_kernels.cc's TensorListReserve`, `num_elements` is assumed to be a tensor of size 1. When a `num_elements` of more than 1 element is provided, then `tf.raw_ops.TensorListReserve` fails the `CHECK_EQ` in `CheckIsAlignedAndSingleElement`. We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Weakness: CWE-617
Which versions are affected by CVE-2022-35960?
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 | From 2.7.0 to 2.8.0 | 2.7.2 |
tensorflow PyPI | All versions | 2.7.2, 2.8.1, 2.9.1 |
tensorflow PyPI | All versions | 2.7.2 |
tensorflow PyPI | All versions | 2.7.2 |
tensorflow PyPI | From 2.8.0 | 2.8.1 |
tensorflow PyPI | From 2.8.0 | 2.8.1 |
16 more packages
tensorflow PyPI | From 2.9.0 | 2.9.1 |
tensorflow PyPI | From 2.9.0 | 2.9.1 |
tensorflow-cpu PyPI | All versions | 2.7.2, 2.8.1, 2.9.1 |
tensorflow-cpu PyPI | All versions | 2.7.2 |
tensorflow-cpu PyPI | All versions | 2.7.2 |
tensorflow-cpu PyPI | From 2.8.0 | 2.8.1 |
tensorflow-cpu PyPI | From 2.8.0 | 2.8.1 |
tensorflow-cpu PyPI | From 2.9.0 | 2.9.1 |
tensorflow-cpu PyPI | From 2.9.0 | 2.9.1 |
tensorflow-gpu PyPI | All versions | 2.7.2, 2.8.1, 2.9.1 |
tensorflow-gpu PyPI | All versions | 2.7.2 |
tensorflow-gpu PyPI | All versions | 2.7.2 |
tensorflow-gpu PyPI | From 2.8.0 | 2.8.1 |
tensorflow-gpu PyPI | From 2.8.0 | 2.8.1 |
tensorflow-gpu PyPI | From 2.9.0 | 2.9.1 |
tensorflow-gpu PyPI | From 2.9.0 | 2.9.1 |
Products include Google Tensorflow.
How do I fix CVE-2022-35960?
Upgrade tensorflow to a fixed version for your release line: 2.7.2, 2.8.1 or 2.9.1.
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-2022-35960 being exploited?
There is no known exploitation of CVE-2022-35960 in the wild and no public exploit code.
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-2022-35960, GHSA-v5xg-3q2c-c2r4, PYSEC-2026-1036, PYSEC-2026-3243, PYSEC-2026-3370.