TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_gradient` receives input `min` or `max` that is nonscalar, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. 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.
References
Link | Resource |
---|---|
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r26c-679w-mrjm | Third Party Advisory |
https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feed | Patch Third Party Advisory |
Configurations
Configuration 1 (hide)
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Information
Published : 2022-09-16 16:15
Updated : 2022-09-20 07:42
NVD link : CVE-2022-36005
Mitre link : CVE-2022-36005
JSON object : View
CWE
CWE-617
Reachable Assertion
Products Affected
- tensorflow