CVE-2021-37662: Reference binding to nullptr in boosted trees in TensorFlow
Impact An attacker can generate undefined behavior via a reference binding to nullptr in BoostedTreesCalculateBestGainsPerFeature:
python import tensorflow as tf
tf.rawops.BoostedTreesCalculateBestGainsPerFeature( nodeidrange=[], statssummarylist=[[1,2,3]], l1=[1.0], l2=[1.0], treecomplexity =[1.0], minnodeweight =[1.17], maxsplits=5)
A similar attack can occur in BoostedTreesCalculateBestFeatureSplitV2:
python import tensorflow as tf tf.rawops.BoostedTreesCalculateBestFeatureSplitV2( nodeidrange=[], statssummarieslist=[[1,2,3]], splittypes=[''], candidatefeatureids=[1,2,3,4], l1=[1], l2=[1], treecomplexity=[1.0], minnodeweight=[1.17], logitsdimension=5) The implementation does not validate the input values.
Patches We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit. 429f009d2b2c09028647dd4bb7b3f6f414bbaad7.
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 generate undefined behavior via a reference binding to nullptr in BoostedTreesCalculateBestGainsPerFeature and similar attack can occur in BoostedTreesCalculateBestFeatureSplitV2. The implementation does not validate the input values. We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit 429f009d2b2c09028647dd4bb7b3f6f414bbaad7. 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
tensorflow/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 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad - Upgrade
Upgrade to a fixed release to a version that resolves this vulnerability.
Patch 429f009d2b2c09028647dd4bb7b3f6f414bbaad7 - Upgrade
Upgrade
tensorflow/tensorflowto a version that resolves this vulnerability.Fixed in 2.5.1 - Upgrade
Upgrade
tensorflow/tensorflowto a version that resolves this vulnerability.Fixed in 2.4.3 - Upgrade
Upgrade
tensorflow/tensorflowto a version that resolves this vulnerability.Fixed in 2.3.4
Event History
Frequently Asked Questions
What is the severity of CVE-2021-37662?
CVE-2021-37662 is classified as a high-severity vulnerability due to its potential for causing undefined behavior in TensorFlow.
How do I fix CVE-2021-37662?
To fix CVE-2021-37662, upgrade TensorFlow to version 2.3.5, 2.4.3, or 2.5.1.
What software is affected by CVE-2021-37662?
CVE-2021-37662 affects TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, and 2.5.0.
What impact does CVE-2021-37662 have on users?
CVE-2021-37662 may lead to crashes or unexpected behavior in applications using affected versions of TensorFlow.
Is there a workaround for CVE-2021-37662?
There is no specific workaround for CVE-2021-37662; the recommended action is to update to the patched versions.