Vulnerability CVE-2022-41894

Vulnerability Name:

CVE-2022-41894 (CCN-240390)

Assigned:

2022-11-18

Published:

2022-11-18

Updated:

2022-11-22

Summary:

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.

CVSS v3 Severity:

8.1 High (CVSS v3.1 Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H)
7.1 High (Temporal CVSS v3.1 Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H/E:U/RL:O/RC:C)

Exploitability Metrics:	Attack Vector (AV): Network Attack Complexity (AC): High Privileges Required (PR): None User Interaction (UI): None
Scope:	Scope (S): Unchanged
Impact Metrics:	Confidentiality (C): High Integrity (I): High Availibility (A): High

7.1 High (CCN CVSS v3.1 Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H)
6.2 Medium (CCN Temporal CVSS v3.1 Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H/E:U/RL:O/RC:C)

Exploitability Metrics:	Attack Vector (AV): Network Attack Complexity (AC): High Privileges Required (PR): Low User Interaction (UI): Required
Scope:	Scope (S): Unchanged
Impact Metrics:	Confidentiality (C): High Integrity (I): High Availibility (A): High

CVSS v2 Severity:

7.1 High (CCN CVSS v2 Vector: AV:N/AC:H/Au:S/C:C/I:C/A:C)

Exploitability Metrics:	Access Vector (AV): Network Access Complexity (AC): High Athentication (Au): Single_Instance
Impact Metrics:	Confidentiality (C): Complete Integrity (I): Complete Availibility (A): Complete

Vulnerability Type:

CWE-120

Vulnerability Consequences:

Gain Access

References:

Source: MITRE
Type: CNA
CVE-2022-41894

Source: XF
Type: UNKNOWN
tensorflow-cve202241894-bo(240390)

Source: CCN
Type: TensorFlow GIT Repository
Buffer overflow in CONV_3D_TRANSPOSE on TFLite

Source: CCN
Type: IBM Security Bulletin 6855117 (Watson Discovery)
IBM Watson Discovery Cartridge for IBM Cloud Pak for Data affected by vulnerability in TensorFlow

Source: CCN
Type: IBM Security Bulletin 6921283 (Robotic Process Automation for Cloud Pak)
Multiple Security Vulnerabilities may affect IBM Robotic Process Automation for Cloud Pak.

Source: CCN
Type: IBM Security Bulletin 7001747 (Maximo Application Suite)
tensorflow-2.7.3-cp37 vulnerable to CVE-2022-41911 CVE-2022-41907 CVE-2022-41908 CVE-2022-41896 CVE-2022-41891 CVE-2022-41894 CVE-2022-41884 IBM Maximo Application Suite - Monitor Component

Source: CCN
Type: IBM Security Bulletin 7010075 (Watson Assistant for Cloud Pak for Data)
IBM Watson Assistant for IBM Cloud Pak for Data is vulnerable to multiple vulerabilities in TensorFlow

Source: CCN
Type: Mend Vulnerability Database
CVE-2022-41894

Vulnerable Configuration:

Configuration CCN 1:

cpe:/a:google:tensorflow:2.10.0:*:*:*:*:*:*:*

AND

cpe:/a:ibm:robotic_process_automation_for_cloud_pak:21.0.1:*:*:*:*:*:*:*

OR cpe:/a:ibm:robotic_process_automation_for_cloud_pak:21.0.7:*:*:*:*:*:*:*

Denotes that component is vulnerable

BACK