CVE-2022-35996 Floating point exception in `Conv2D` in TensorFlow
Attackers can cause a denial of service in TensorFlow by triggering a division-by-zero error in Conv2D operations with empty inputs.
- Exploited in the wild
- Not known
- Login needed
- Not needed
- Attackable
- Over the internet
- Victim action needed
- Not needed
- Fix
- Available
What is CVE-2022-35996?
CVE-2022-35996 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. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. 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-369
Which versions are affected by CVE-2022-35996?
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 | 2.7.2, 2.8.1, 2.9.1 |
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-2022-35996?
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-2022-35996 being exploited?
There is no known exploitation of CVE-2022-35996 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-2022-35996, GHSA-q5jv-m6qw-5g37, PYSEC-2026-1029, PYSEC-2026-3228, PYSEC-2026-3361.