Buffer overflow in Google Tensorflow

CVE-2021-29520

TensorFlow is an end-to-end open source platform for machine learning. Missing validation between arguments to `tf.raw_ops.Conv3DBackprop*` operations can result in heap buffer overflows. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/4814fafb0ca6b5ab58a09411523b2193fed23fed/tensorflow/core/kernels/conv_grad_shape_utils.cc#L94-L153) assumes that the `input`, `filter_sizes` and `out_backprop` tensors have the same shape, as they are accessed in parallel. 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.

Vulnerability class: Buffer Overflow

EPSS: 0.002 (13.3th 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)

Public proof-of-concept exploits

References

Frequently asked questions

What is CVE-2021-29520?
CVE-2021-29520 is a low-severity vulnerability in Google Tensorflow, classified under Buffer Copy without Checking Size of Input (Classic Buffer Overflow). CVSS score: 2.5/10. Published 2021-05-14.
How severe is CVE-2021-29520?
Low severity. CVSS v3 base score is 2.5 out of 10.
Is CVE-2021-29520 known to be exploited?
1 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.