CVE-2022-23583 `CHECK`-failures in binary ops in Tensorflow
A malicious user can cause a denial of service in TensorFlow by altering a SavedModel to trigger CHECK failures via type confusion in binary operations.
- Exploited in the wild
- Not known
- Login needed
- Any signed-in user
- Attackable
- Over the internet
- Victim action needed
- Not needed
- Fix
- Available
What is CVE-2022-23583?
CVE-2022-23583 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 4 Feb 2022. Any signed-in user can exploit it over the network, with no action from the victim.
Official description
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that any binary op would trigger `CHECK` failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the `dtype` no longer matches the `dtype` expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. If `Tin` and `Tout` don't match the type of data in `out` and `input_*` tensors then `flat<*>` would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a `CHECK` crash, hence a denial of service. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Which versions are affected by CVE-2022-23583?
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 | 2.5.3, 2.6.3, 2.7.1 |
tensorflow PyPI | All versions | 2.5.3, 2.6.3, 2.7.1 |
tensorflow PyPI | All versions | 2.5.3 |
tensorflow PyPI | All versions | 2.5.3 |
tensorflow PyPI | From 2.6.0 | 2.6.3 |
tensorflow PyPI | From 2.6.0 | 2.6.3 |
16 more packages
tensorflow PyPI | From 2.7.0 | 2.7.1 |
tensorflow PyPI | From 2.7.0 | 2.7.1 |
tensorflow-cpu PyPI | All versions | 2.5.3, 2.6.3 |
tensorflow-cpu PyPI | All versions | 2.5.3 |
tensorflow-cpu PyPI | All versions | 2.5.3 |
tensorflow-cpu PyPI | From 2.6.0 | 2.6.3 |
tensorflow-cpu PyPI | From 2.6.0 | 2.6.3 |
tensorflow-cpu PyPI | From 2.7.0 | 2.7.1 |
tensorflow-cpu PyPI | From 2.7.0 | 2.7.1 |
tensorflow-gpu PyPI | All versions | 2.5.3, 2.6.3 |
tensorflow-gpu PyPI | All versions | 2.5.3 |
tensorflow-gpu PyPI | All versions | 2.5.3 |
tensorflow-gpu PyPI | From 2.6.0 | 2.6.3 |
tensorflow-gpu PyPI | From 2.6.0 | 2.6.3 |
tensorflow-gpu PyPI | From 2.7.0 | 2.7.1 |
tensorflow-gpu PyPI | From 2.7.0 | 2.7.1 |
Products include Google Tensorflow.
How do I fix CVE-2022-23583?
Upgrade tensorflow to a fixed version for your release line: 2.5.3, 2.6.3 or 2.7.1.
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-2022-23583 being exploited?
It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-23583 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-2022-23583, GHSA-gjqc-q9g6-q2j3, PYSEC-2022-147, PYSEC-2022-92, PYSEC-2026-3191.