Vulnerability in Google Tensorflow

CVE-2022-35960

TensorFlow is an open source platform for machine learning. In `core/kernels/list_kernels.cc's TensorListReserve`, `num_elements` is assumed to be a tensor of size 1. When a `num_elements` of more than 1 element is provided, then `tf.raw_ops.TensorListReserve` fails the `CHECK_EQ` in `CheckIsAlignedAndSingleElement`. We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. 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: 0.006 (43.7th 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

Weakness classification (CWE)

Public proof-of-concept exploits

References

Frequently asked questions

What is CVE-2022-35960?
CVE-2022-35960 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-2022-35960?
Medium severity. CVSS v3 base score is 5.9 out of 10.
Is CVE-2022-35960 known to be exploited?
2 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.