CVE-2021-37643: Null pointer dereference in `MatrixDiagPartOp` in TensorFlow
Impact If a user does not provide a valid padding value to tf.rawops.MatrixDiagPartOp, then the code triggers a null pointer dereference (if input is empty) or produces invalid behavior, ignoring all values after the first:
python import tensorflow as tf
tf.rawops.MatrixDiagPartV2( input=tf.ones(2,dtype=tf.int32), k=tf.ones(2,dtype=tf.int32), paddingvalue=[])
Although this example is given for MatrixDiagPartV2, all versions of the operation are affected.
The implementation reads the first value from a tensor buffer without first checking that the tensor has values to read from.
Patches We have patched the issue in GitHub commit 482da92095c4d48f8784b1f00dda4f81c28d2988.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
Other sources
TensorFlow is an end-to-end open source platform for machine learning. If a user does not provide a valid padding value to tf.rawops.MatrixDiagPartOp, then the code triggers a null pointer dereference (if input is empty) or produces invalid behavior, ignoring all values after the first. The implementation reads the first value from a tensor buffer without first checking that the tensor has values to read from. We have patched the issue in GitHub commit 482da92095c4d48f8784b1f00dda4f81c28d2988. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Affected Software
Remediation
Recommended actions to resolve this vulnerability, in priority order.
- Upgrade
Upgrade
pip/tensorflow-gputo a version that resolves this vulnerability.Fixed in 2.5.1 - Upgrade
Upgrade
pip/tensorflow-gputo a version that resolves this vulnerability.Fixed in 2.4.3 - Upgrade
Upgrade
pip/tensorflow-gputo a version that resolves this vulnerability.Fixed in 2.3.4 - Upgrade
Upgrade
pip/tensorflow-cputo a version that resolves this vulnerability.Fixed in 2.5.1 - Upgrade
Upgrade
pip/tensorflow-cputo a version that resolves this vulnerability.Fixed in 2.4.3 - Upgrade
Upgrade
pip/tensorflow-cputo a version that resolves this vulnerability.Fixed in 2.3.4 - Upgrade
Upgrade
pip/tensorflowto a version that resolves this vulnerability.Fixed in 2.5.1 - Upgrade
Upgrade
pip/tensorflowto a version that resolves this vulnerability.Fixed in 2.4.3 - Upgrade
Upgrade
pip/tensorflowto a version that resolves this vulnerability.Fixed in 2.3.4 - Upgrade
Upgrade
tensorflowto a version that resolves this vulnerability.Fixed in 2.6.0Patch GitHub commit 482da92095c4d48f8784b1f00dda4f81c28d2988 - Upgrade
Upgrade
tensorflowto a version that resolves this vulnerability.Fixed in 2.5.1Patch GitHub commit 482da92095c4d48f8784b1f00dda4f81c28d2988 - Upgrade
Upgrade
tensorflowto a version that resolves this vulnerability.Fixed in 2.4.3Patch GitHub commit 482da92095c4d48f8784b1f00dda4f81c28d2988 - Upgrade
Upgrade
tensorflowto a version that resolves this vulnerability.Fixed in 2.3.4Patch GitHub commit 482da92095c4d48f8784b1f00dda4f81c28d2988 - Compensating control
If using tf.raw_ops.MatrixDiagPartOp / MatrixDiagPartV2, ensure users provide a valid padding value (avoid invalid/empty padding values) to prevent null pointer dereference and invalid behavior.
Event History
Frequently Asked Questions
What is the severity of CVE-2021-37643?
CVE-2021-37643 has been classified as a medium severity vulnerability due to the potential for null pointer dereference and unexpected behavior.
How do I fix CVE-2021-37643?
To remediate CVE-2021-37643, upgrade to TensorFlow version 2.5.1, 2.4.3, or 2.3.4 or a later version.
What software is affected by CVE-2021-37643?
CVE-2021-37643 affects Google TensorFlow versions from 2.3.0 to 2.6.0-rc2.
What is the potential impact of CVE-2021-37643?
The impact of CVE-2021-37643 can lead to application crashes or unintended data processing behavior due to unhandled null pointers.
Is CVE-2021-37643 specific to TensorFlow GPU or CPU?
CVE-2021-37643 affects both TensorFlow GPU and CPU installations across the specified versions.