CVE-2021-37658: Reference binding to nullptr in `MatrixSetDiagV*` ops in TensorFlow
Impact An attacker can cause undefined behavior via binding a reference to null pointer in all operations of type tf.rawops.MatrixSetDiagV:
python import tensorflow as tf
tf.rawops.MatrixSetDiagV3( input=[1,2,3], diagonal=[1,1], k=[], align='RIGHTLEFT') The implementation has incomplete validation that the value of k is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong:
cc auto& diagindex = context->input(1); ... lowerdiagindex = diagindex.flat<int32>()(0); Patches We have patched the issue in GitHub commit ff8894044dfae5568ecbf2ed514c1a37dc394f1b.
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. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type tf.rawops.MatrixSetDiagV. The implementation has incomplete validation that the value of k is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit ff8894044dfae5568ecbf2ed514c1a37dc394f1b. 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
Event History
Frequently Asked Questions
What is the severity of CVE-2021-37658?
CVE-2021-37658 has been classified with a high severity due to the potential for undefined behavior in TensorFlow operations.
How do I fix CVE-2021-37658?
To fix CVE-2021-37658, update TensorFlow to version 2.5.1 or later, or use the recommended versions depending on your current TensorFlow version.
Which versions of TensorFlow are affected by CVE-2021-37658?
CVE-2021-37658 affects TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, 2.5.0, and the release candidates of 2.6.0.
What operations are vulnerable in CVE-2021-37658?
The vulnerability in CVE-2021-37658 specifically affects the `tf.raw_ops.MatrixSetDiagV*` operations.
Can CVE-2021-37658 cause any data loss?
While CVE-2021-37658 may lead to undefined behavior, it is not specifically designed to cause data loss but may result in unpredictable application behavior.