CVE-2022-21733: Memory exhaustion in Tensorflow
Impact The implementation of StringNGrams can be used to trigger a denial of service attack by causing an OOM condition after an integer overflow:
python import tensorflow as tf
tf.rawops.StringNGrams( data=['123456'], datasplits=[0,1], separator='a'15, ngramwidths=[], leftpad='', rightpad='', padwidth=-5, preserveshortsequences=True)
We are missing a validation on padwitdh and that result in computing a negative value for ngramwidth which is later used to allocate parts of the output.
Patches We have patched the issue in GitHub commit f68fdab93fb7f4ddb4eb438c8fe052753c9413e8.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Yu Tian of Qihoo 360 AIVul Team.
Other sources
Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on padwitdh and that result in computing a negative value for ngramwidth which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Affected Software
Remediation
Event History
Frequently Asked Questions
What is the severity of CVE-2022-21733?
CVE-2022-21733 has high severity due to its potential to cause a denial of service through out-of-memory conditions.
How do I fix CVE-2022-21733?
To fix CVE-2022-21733, you should upgrade to TensorFlow version 2.5.3, 2.6.3, or 2.7.1 depending on your current version.
Which versions of TensorFlow are affected by CVE-2022-21733?
CVE-2022-21733 affects TensorFlow versions up to 2.5.2 and between 2.6.0 to 2.6.2, as well as 2.7.0.
What type of attack does CVE-2022-21733 enable?
CVE-2022-21733 enables a denial of service attack by triggering an out-of-memory condition.
Is CVE-2022-21733 related to a specific TensorFlow component?
Yes, CVE-2022-21733 is related to the implementation of 'StringNGrams' in TensorFlow.