CVE-2022-23589 Null pointer dereference in Grappler's `IsConstant` in Tensorflow
Attackers can cause a denial of service in TensorFlow by providing a maliciously altered SavedModel file that triggers a null pointer dereference.
- 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-2022-23589?
CVE-2022-23589 is a medium-severity 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, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a `SavedModel` file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the `GraphDef` might not have the required nodes for the binary operation. If a node is missing, the correposning `mul_*child` would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during `IsIdentityConsumingSwitch`. 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.
Weakness: CWE-476
Which versions are affected by CVE-2022-23589?
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-2022-23589?
Upgrade tensorflow to a fixed version for your release line: 2.5.3, 2.6.3 or 2.7.1.
Is CVE-2022-23589 being exploited?
It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-23589 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-2022-23589, GHSA-9px9-73fg-3fqp, PYSEC-2022-153, PYSEC-2022-98, PYSEC-2026-3154.