CVE-2022-36012: Assertion fail on MLIR empty edge names in TensorFlow
TensorFlow is an open source platform for machine learning. When mlir::tfg::ConvertGenericFunctionToFunctionDef is given empty function attributes, it crashes. We have patched the issue in GitHub commit ad069af92392efee1418c48ff561fd3070a03d7b. 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.
Affected Software
Remediation
Event History
Frequently Asked Questions
What is CVE-2022-36012?
CVE-2022-36012 is a vulnerability in TensorFlow, an open source platform for machine learning, that can cause a crash when empty function attributes are used in mlir::tfg::ConvertGenericFunctionToFunctionDef.
What is the severity of CVE-2022-36012?
The severity of CVE-2022-36012 is high, with a severity value of 7.5.
Which software versions are affected by CVE-2022-36012?
Versions 2.7.2 to 2.9.1 of Google TensorFlow, as well as versions 2.10-rc0, 2.10-rc1, 2.10-rc2, and 2.10-rc3 are affected by CVE-2022-36012.
Has a fix been released for CVE-2022-36012?
Yes, a fix for CVE-2022-36012 has been released in GitHub commit ad069af92392efee1418c48ff561fd3070a03d7b. The fix will be included in TensorFlow 2.10.0.
How can I find more information about CVE-2022-36012?
You can find more information about CVE-2022-36012 on the TensorFlow GitHub page and the associated security advisories: GHSA-jvhc-5hhr-w3v5.