CVE-2022-35952: `CHECK` failures in `UnbatchGradOp` in TensorFlow
TensorFlow is an open source platform for machine learning. The UnbatchGradOp function takes an argument id that is assumed to be a scalar. A nonscalar id can trigger a CHECK failure and crash the program. It also requires its argument batchindex to contain three times the number of elements as indicated in its batchindex.dimsize(0). An incorrect batchindex can trigger a CHECK failure and crash the program. We have patched the issue in GitHub commit 5f945fc6409a3c1e90d6970c9292f805f6e6ddf2. 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 the severity of CVE-2022-35952?
CVE-2022-35952 has a medium severity rating due to its ability to cause a program crash.
How do I fix CVE-2022-35952?
To fix CVE-2022-35952, upgrade TensorFlow to a version that is not affected, such as 2.10 or later.
What versions of TensorFlow are affected by CVE-2022-35952?
CVE-2022-35952 affects TensorFlow versions from 2.7.0 to 2.9.1 and certain release candidates of 2.10.
What does CVE-2022-35952 affect in TensorFlow?
CVE-2022-35952 affects the `UnbatchGradOp` function, which can cause program crashes if given nonscalar arguments.
Is CVE-2022-35952 a remote exploit?
CVE-2022-35952 is not a remote exploit; it requires local execution of TensorFlow with specific arguments.