Attacker Value
Unknown
(0 users assessed)
Exploitability
Unknown
(0 users assessed)
User Interaction
None
Privileges Required
Low
Attack Vector
Local
0

CVE-2021-29580

Disclosure Date: May 14, 2021
Add MITRE ATT&CK tactics and techniques that apply to this CVE.

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.

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CVSS V3 Severity and Metrics
Base Score:
5.5 Medium
Impact Score:
3.6
Exploitability Score:
1.8
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Attack Vector (AV):
Local
Attack Complexity (AC):
Low
Privileges Required (PR):
Low
User Interaction (UI):
None
Scope (S):
Unchanged
Confidentiality (C):
None
Integrity (I):
None
Availability (A):
High

General Information

Vendors

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Weaknesses

Additional Info

Technical Analysis