CVE-2022-35986 Segfault in `RaggedBincount` in TensorFlow
An attacker can cause a segmentation fault and denial of service by providing an empty input tensor to the RaggedBincount operation in TensorFlow.
- Exploited in the wild
- Not known
- Login needed
- Not needed
- Attackable
- Over the internet
- Victim action needed
- Not needed
- Fix
- Available
What is CVE-2022-35986?
CVE-2022-35986 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 `RaggedBincount` is given an empty input tensor `splits`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7a4591fd4f065f4fa903593bc39b2f79530a74b8. 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-20
Which versions are affected by CVE-2022-35986?
8 open source packages ship an affected version, including tensorflow. 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 |
2 more packages
tensorflow PyPI | From 2.9.0 | 2.9.1 |
tensorflow PyPI | From 2.9.0 | 2.9.1 |
Products include Google Tensorflow.
How do I fix CVE-2022-35986?
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-2022-35986 being exploited?
There is no known exploitation of CVE-2022-35986 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-2022-35986, GHSA-wr9v-g9vf-c74v, PYSEC-2026-938.