CVE-2021-41217: Null pointer exception when `Exit` node is not preceded by `Enter` op
Impact The process of building the control flow graph for a TensorFlow model is vulnerable to a null pointer exception when nodes that should be paired are not: python import tensorflow as tf @tf.function def func(): return tf.rawops.Exit(data=[False,False]) func()
This occurs because the code assumes that the first node in the pairing (e.g., an Enter node) always exists when encountering the second node (e.g., an Exit node): cc ... } else if (IsExit(currnode)) { // Exit to the parent frame. parent = parentnodes[currid]; framename = cfinfo->framenames[parent->id()]; ...
When this is not the case, parent is nullptr so dereferencing it causes a crash.
Patches We have patched the issue in GitHub commit 05cbebd3c6bb8f517a158b0155debb8df79017ff.
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 open source platform for machine learning. In affected versions the process of building the control flow graph for a TensorFlow model is vulnerable to a null pointer exception when nodes that should be paired are not. This occurs because the code assumes that the first node in the pairing (e.g., an Enter node) always exists when encountering the second node (e.g., an Exit node). When this is not the case, parent is nullptr so dereferencing it causes a crash. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Affected Software
Remediation
Event History
Frequently Asked Questions
What is the severity of CVE-2021-41217?
CVE-2021-41217 is classified as a high severity vulnerability due to its potential to cause application crashes.
How do I fix CVE-2021-41217?
To mitigate CVE-2021-41217, update TensorFlow to version 2.4.4, 2.5.2, or 2.6.1.
What components are affected by CVE-2021-41217?
CVE-2021-41217 affects TensorFlow and TensorFlow GPU packages from versions earlier than 2.4.4.
Can CVE-2021-41217 be exploited remotely?
CVE-2021-41217 may be exploited remotely if malicious inputs are used to build a TensorFlow model.
Is a workaround available for CVE-2021-41217?
No official workaround is available for CVE-2021-41217, upgrading to the patched versions is recommended.