CVE-2022-36017: Segfault in `Requantize` in TensorFlow
First published: Fri Sep 16 2022(Updated: )
TensorFlow is an open source platform for machine learning. If `Requantize` is given `input_min`, `input_max`, `requested_output_min`, `requested_output_max` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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.
Credit: security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| Google TensorFlow | <2.7.2 | |
| Google TensorFlow | >=2.8.0<2.8.1 | |
| Google TensorFlow | >=2.9.0<2.9.1 | |
| Google TensorFlow | =2.10-rc0 | |
| Google TensorFlow | =2.10-rc1 | |
| Google TensorFlow | =2.10-rc2 | |
| Google TensorFlow | =2.10-rc3 |
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Reference Links
Frequently Asked Questions
What is CVE-2022-36017?
CVE-2022-36017 is a vulnerability in TensorFlow that can be used to trigger a denial of service attack.
How does CVE-2022-36017 affect TensorFlow?
CVE-2022-36017 affects TensorFlow versions up to and including 2.7.2, 2.8.0 - 2.8.1, 2.9.0 - 2.9.1, and 2.10-rc0 - 2.10-rc3.
What is the severity of CVE-2022-36017?
CVE-2022-36017 has a severity score of 7.5 (high).
How can CVE-2022-36017 be exploited?
CVE-2022-36017 can be exploited by providing specific input tensors to the Requantize function in TensorFlow, resulting in a segfault and potential denial of service.
Has CVE-2022-36017 been patched?
Yes, CVE-2022-36017 has been patched in TensorFlow. Please refer to the GitHub security advisories for more information.
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