CVE-2022-36005
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.
Does this matter?
High impact if exploited, but EPSS currently rates exploitation as unlikely (0.42%). Schedule it in the normal patch cycle and watch for a rise in EPSS or a public exploit.
Description
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.
- CVSS 3.1
- 7.5 HIGHCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
- EPSS
- 0.42% probability · 36th percentile
- CISA KEV
- Not listed
- Weakness
- CWE-617
- Affected
- google/tensorflow
- Source
- security-advisories@github.com
References
- https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feedPatch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r26c-679w-mrjmThird Party Advisory
- https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feedPatch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r26c-679w-mrjmThird Party Advisory
Source: NVD record, EPSS from FIRST.org, KEV from CISA. Refreshed daily.