CVE-2022-35965: Segfault in `LowerBound` and `UpperBound` in TensorFlow
TensorFlow is an open source platform for machine learning. If LowerBound or UpperBound is given an emptysortedinputs input, it results in a nullptr dereference, leading to a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bce3717eaef4f769019fd18e990464ca4a2efeea. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Affected Software
Remediation
Event History
Frequently Asked Questions
What is the severity of CVE-2022-35965?
CVE-2022-35965 is classified as a denial of service vulnerability due to a nullptr dereference.
How do I fix CVE-2022-35965?
To fix CVE-2022-35965, update TensorFlow to a patched version beyond 2.10-rc3.
What causes CVE-2022-35965 in TensorFlow?
CVE-2022-35965 occurs when the LowerBound or UpperBound functions are given an empty sorted_inputs, leading to a segmentation fault.
Which versions of TensorFlow are affected by CVE-2022-35965?
TensorFlow versions from 2.7.0 up to 2.10-rc3 are affected by CVE-2022-35965.
Can CVE-2022-35965 lead to data breaches?
CVE-2022-35965 primarily leads to denial of service and does not directly enable data breaches.