CVE-2022-36000: Null dereference on MLIR on empty function attributes in TensorFlow
First published: Fri Sep 16 2022(Updated: )
TensorFlow is an open source platform for machine learning. When `mlir::tfg::ConvertGenericFunctionToFunctionDef` is given empty function attributes, it gives a null dereference. We have patched the issue in GitHub commit aed36912609fc07229b4d0a7b44f3f48efc00fd0. 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.
Credit: security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| TensorFlow Keras | <2.7.2 | |
| TensorFlow Keras | >=2.8.0<2.8.1 | |
| TensorFlow Keras | >=2.9.0<2.9.1 | |
| TensorFlow Keras | =2.10-rc0 | |
| TensorFlow Keras | =2.10-rc1 | |
| TensorFlow Keras | =2.10-rc2 | |
| TensorFlow Keras | =2.10-rc3 |
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Reference Links
Frequently Asked Questions
What is the severity of CVE-2022-36000?
CVE-2022-36000 has a medium severity level due to the potential for a null dereference when empty function attributes are provided.
Which versions of TensorFlow are affected by CVE-2022-36000?
CVE-2022-36000 affects TensorFlow versions prior to 2.7.2 and versions 2.8.0 to 2.8.1, 2.9.0 to 2.9.1, and specific release candidates of 2.10.
How do I fix CVE-2022-36000?
To fix CVE-2022-36000, update your TensorFlow installation to version 2.10-rc4 or later.
What impact does CVE-2022-36000 have on TensorFlow applications?
CVE-2022-36000 can cause TensorFlow applications to crash or behave unexpectedly due to a null dereference.
Is there a patch for CVE-2022-36000?
Yes, CVE-2022-36000 has been patched in a GitHub commit and is included in later versions of TensorFlow.
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