Google TensorFlow up to 2.8.3/2.9.2/2.10.0 control flow

CVSS Meta Temp Score
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CTI Interest Score
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5.1$0-$5k0.00

Summaryinfo

A vulnerability classified as problematic has been found in Google TensorFlow up to 2.8.3/2.9.2/2.10.0. This affects an unknown function. The manipulation leads to control flow. This vulnerability is uniquely identified as CVE-2022-41884. The attack is possible to be carried out remotely. No exploit exists. It is recommended to upgrade the affected component.

Detailsinfo

A vulnerability was found in Google TensorFlow up to 2.8.3/2.9.2/2.10.0 (Artificial Intelligence Software). It has been rated as problematic. This issue affects some unknown processing. The manipulation with an unknown input leads to a control flow vulnerability. Using CWE to declare the problem leads to CWE-670. The code contains a control flow path that does not reflect the algorithm that the path is intended to implement, leading to incorrect behavior any time this path is navigated. Impacted is availability. The summary by CVE is:

TensorFlow is an open source platform for machine learning. If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784. 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.

The weakness was disclosed 11/19/2022 as GHSA-jq6x-99hj-q636. It is possible to read the advisory at github.com. The identification of this vulnerability is CVE-2022-41884 since 09/30/2022. It demands that the victim is doing some kind of user interaction. The technical details are unknown and an exploit is not publicly available.

Upgrading to version 2.8.4, 2.9.3, 2.10.1 or 2.11 eliminates this vulnerability. Applying the patch 2b56169c16e375c521a3bc8ea658811cc0793784 is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Type

Vendor

Name

Version

License

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 5.1
VulDB Meta Temp Score: 5.1

VulDB Base Score: 3.1
VulDB Temp Score: 3.0
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 7.5
NVD Vector: 🔍

CNA Base Score: 4.8
CNA Vector (GitHub, Inc.): 🔍

CVSSv2info

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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍

Exploitinginfo

Class: Control flow
CWE: CWE-670
CAPEC: 🔍
ATT&CK: 🔍

Physical: No
Local: No
Remote: Yes

Availability: 🔍
Status: Not defined

EPSS Score: 🔍
EPSS Percentile: 🔍

Price Prediction: 🔍
Current Price Estimation: 🔍

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: Upgrade
Status: 🔍

0-Day Time: 🔍

Upgrade: TensorFlow 2.8.4/2.9.3/2.10.1/2.11
Patch: 2b56169c16e375c521a3bc8ea658811cc0793784

Timelineinfo

09/30/2022 🔍
11/19/2022 +50 days 🔍
11/19/2022 +0 days 🔍
12/20/2022 +31 days 🔍

Sourcesinfo

Vendor: google.com

Advisory: GHSA-jq6x-99hj-q636
Status: Confirmed

CVE: CVE-2022-41884 (🔍)
GCVE (CVE): GCVE-0-2022-41884
GCVE (VulDB): GCVE-100-213947

Entryinfo

Created: 11/19/2022 08:26
Updated: 12/20/2022 13:04
Changes: 11/19/2022 08:26 (52), 12/20/2022 13:04 (12)
Complete: 🔍
Cache ID: 216::103

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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