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CVE-2021-29580

nvd nist
Published: May 14, 2021Modified: Nov 21, 2024

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5.5
Vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Exploitability: 1.8 / Impact: 3.6
Source: NVD

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.

Affected (4)

Products: Google: Tensorflow
1 product
Tensorflow
Configuration A
4 vulnerable
Vulnerable SoftwareAffected Versions
Google
Before 2.1.4
From 2.2.0 to 2.2.3
From 2.3.0 to 2.3.3
From 2.4.0 to 2.4.2

References (4)

Source: security-advisories@github.com
PatchThird Party Advisory
Source: security-advisories@github.com
ExploitPatchThird Party Advisory
Source: af854a3a-2127-422b-91ae-364da2661108
PatchThird Party Advisory
Source: af854a3a-2127-422b-91ae-364da2661108
ExploitPatchThird Party Advisory

Timeline

No history available yet.