Vulnerability in Google Tensorflow

CVE-2021-29580

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

EPSS: 0.002 (8.9th percentile) — read the EPSS interpretation.

CVSS v3 metric

CVSS v3 base score 2.5 (Low). Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L.

Affected products

Weakness classification (CWE)

References

Frequently asked questions

What is CVE-2021-29580?
CVE-2021-29580 is a low-severity vulnerability in Google Tensorflow, classified under Use of Uninitialized Resource. CVSS score: 2.5/10. Published 2021-05-14.
How severe is CVE-2021-29580?
Low severity. CVSS v3 base score is 2.5 out of 10.