Vulnerability in Google Tensorflow
CVE-2022-35969
TensorFlow is an open source platform for machine learning. The implementation of `Conv2DBackpropInput` requires `input_sizes` to be 4-dimensional. Otherwise, it gives a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c. 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.
EPSS: 0.004 (32.5th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 5.9 (Medium). Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H.
Affected products
- Google Tensorflow — versions 2.10
- Tensorflow — versions < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1
Weakness classification (CWE)
Public proof-of-concept exploits
References
- security-advisories@github.com (x_refsource_CONFIRM, Patch, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
Frequently asked questions
- What is CVE-2022-35969?
- CVE-2022-35969 is a medium-severity vulnerability in Google Tensorflow, classified under Reachable Assertion. CVSS score: 5.9/10. Published 2022-09-16.
- How severe is CVE-2022-35969?
- Medium severity. CVSS v3 base score is 5.9 out of 10.
- Is CVE-2022-35969 known to be exploited?
- 1 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.