CVE-2022-23572 Crash when type cannot be specialized in Tensorflow
Attackers can cause a crash in TensorFlow by triggering a type specialization failure during shape inference, leading to denial of service.
- 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-2022-23572?
CVE-2022-23572 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. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the `DCHECK` function however, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
Which versions are affected by CVE-2022-23572?
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-2022-23572?
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-2022-23572 being exploited?
It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-23572 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-2022-23572, GHSA-rww7-2gpw-fv6j, PYSEC-2022-136, PYSEC-2022-81, PYSEC-2026-3241.