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

CVE-2021-37665

Disclosure Date: August 12, 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. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The implementation does not validate the dimensions of the input tensor. A similar issue occurs in MklRequantizePerChannelOp. The implementation does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

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CVSS V3 Severity and Metrics
Base Score:
7.8 High
Impact Score:
5.9
Exploitability Score:
1.8
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Attack Vector (AV):
Local
Attack Complexity (AC):
Low
Privileges Required (PR):
Low
User Interaction (UI):
None
Scope (S):
Unchanged
Confidentiality (C):
High
Integrity (I):
High
Availability (A):
High

General Information

Vendors

  • google

Products

  • tensorflow,
  • tensorflow 2.5.0,
  • tensorflow 2.6.0

Additional Info

Technical Analysis