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CVE-2021-29580

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Date: May 14, 2021

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.

Language: Python

Severity Score

Severity Score

Weakness Type (CWE)

Use of Uninitialized Resource

CWE-908

Top Fix

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CVSS v3.1

Base Score:
Attack Vector (AV): LOCAL
Attack Complexity (AC): HIGH
Privileges Required (PR): LOW
User Interaction (UI): NONE
Scope (S): UNCHANGED
Confidentiality (C): NONE
Integrity (I): NONE
Availability (A): LOW

CVSS v2

Base Score:
Access Vector (AV): LOCAL
Access Complexity (AC): LOW
Authentication (AU): NONE
Confidentiality (C): NONE
Integrity (I): NONE
Availability (A): PARTIAL
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