CVE-2022-41891: Segfault in `tf.raw_ops.TensorListConcat` in Tensorflow
TensorFlow is an open source platform for machine learning. If tf.rawops.TensorListConcat is given elementshape=[], it results segmentation fault which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit fc33f3dc4c14051a83eec6535b608abe1d355fde. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Affected Software
Remediation
Recommended actions to resolve this vulnerability, in priority order.
- Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.11Patch fc33f3dc4c14051a83eec6535b608abe1d355fde - Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.10.1Patch fc33f3dc4c14051a83eec6535b608abe1d355fde - Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.9.3Patch fc33f3dc4c14051a83eec6535b608abe1d355fde - Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.8.4Patch fc33f3dc4c14051a83eec6535b608abe1d355fde
Event History
Frequently Asked Questions
What is CVE-2022-41891?
CVE-2022-41891 is a vulnerability in TensorFlow that can be exploited to trigger a denial of service attack by providing a specific input to `tf.raw_ops.TensorListConcat`.
How severe is CVE-2022-41891?
CVE-2022-41891 has a severity value of 7.5 (high).
Which versions of TensorFlow are affected by CVE-2022-41891?
Versions up to and including 2.8.4, 2.9.0 to 2.9.3, and 2.10.0 to 2.10.1 of TensorFlow are affected by CVE-2022-41891.
How can I fix CVE-2022-41891?
You can fix CVE-2022-41891 by updating TensorFlow to version 2.8.5, 2.9.4, or 2.10.2, which include the necessary patch.
Where can I find more information about CVE-2022-41891?
You can find more information about CVE-2022-41891 in the GitHub advisory [GHSA-66vq-54fq-6jvv](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-66vq-54fq-6jvv).