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

CVE-2022-41894

Disclosure Date: November 18, 2022
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Description

TensorFlow is an open source platform for machine learning. The reference kernel of the CONV_3D_TRANSPOSE TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result. Instead of data_ptr += num_channels; it should be data_ptr += output_num_channels; as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels > output_num_channels. An attacker can craft a model with a specific number of input channels. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter. We have patched the issue in GitHub commit 72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

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CVSS V3 Severity and Metrics
Base Score:
8.1 High
Impact Score:
5.9
Exploitability Score:
2.2
Vector:
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H
Attack Vector (AV):
Network
Attack Complexity (AC):
High
Privileges Required (PR):
None
User Interaction (UI):
None
Scope (S):
Unchanged
Confidentiality (C):
High
Integrity (I):
High
Availability (A):
High

General Information

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Weaknesses

Technical Analysis