CVE-2021-37689: Null pointer dereference in TensorFlow Lite MLIR optimizations
Impact An attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service:
This is caused by the MLIR optimization of L2NormalizeReduceAxis operator. The implementation unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements:
cc bool L2NormalizeReduceAxis(Value sqop, DenseElementsAttr axis) { if (sqop.getType().cast<ShapedType>().getRank() - 1 == axis.getValues<int>().begin() || axis.getValues<int>().begin() == -1) { // ... } // ... }
Patches We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955.
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 Yakun Zhang of Baidu Security.
Other sources
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. This is caused by the MLIR optimization of L2NormalizeReduceAxis operator. The implementation unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements. We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955. 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 2.6.0 - Upgrade
Upgrade to a fixed release to a version that resolves this vulnerability.
Patch d6b57f461b39fd1aa8c1b870f1b974aac3554955 - Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.5.1 - Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.4.3 - Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.3.4
Event History
Frequently Asked Questions
What is the severity of CVE-2021-37689?
CVE-2021-37689 is classified as a denial of service vulnerability due to a null pointer dereference.
How do I fix CVE-2021-37689?
To fix CVE-2021-37689, upgrade to TensorFlow version 2.5.1, 2.4.3, or 2.3.4.
Which versions of TensorFlow are affected by CVE-2021-37689?
CVE-2021-37689 affects TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, and specific release candidates of 2.6.0.
What causes the CVE-2021-37689 vulnerability?
The CVE-2021-37689 vulnerability is caused by the MLIR optimization of the L2NormalizeReduceAxis operator.
Can CVE-2021-37689 be exploited remotely?
Yes, CVE-2021-37689 can be exploited remotely by crafting a specific TFLite model.