CVE-2021-29580

LOW

TensorFlow < 2.1.4 - Denial of Service via FractionalMaxPoolGrad Empty Tensor Handling

Title source: llm
STIX 2.1

Description

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.

References (2)

Core 2
Core References
Exploit, Patch, Third Party Advisory x_refsource_confirm
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp

Scores

CVSS v3 2.5
EPSS 0.0019
EPSS Percentile 8.7%
Attack Vector LOCAL
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Details

CWE
CWE-908
Status published
Products (4)
google/tensorflow < 2.1.4
pypi/tensorflow 0 - 2.1.4PyPI
pypi/tensorflow-cpu 0 - 2.1.4PyPI
pypi/tensorflow-gpu 0 - 2.1.4PyPI
Published May 14, 2021
Tracked Since Feb 18, 2026