Warehouse Inventory System 2.0 add_group.php cross-site request forgery

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
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CTI Interest Score
Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
7.2$0-$5k0.00

Summaryinfo

A vulnerability was found in Warehouse Inventory System 2.0 and classified as problematic. This affects an unknown part of the file add_group.php. The manipulation results in cross-site request forgery. This vulnerability is cataloged as CVE-2024-42579. The attack may be launched remotely. Furthermore, there is an exploit available.

Detailsinfo

A vulnerability was found in Warehouse Inventory System 2.0. It has been classified as problematic. Affected is an unknown code of the file add_group.php. The manipulation with an unknown input leads to a cross-site request forgery vulnerability. CWE is classifying the issue as CWE-352. The web application does not, or can not, sufficiently verify whether a well-formed, valid, consistent request was intentionally provided by the user who submitted the request. This is going to have an impact on integrity. CVE summarizes:

A Cross-Site Request Forgery (CSRF) in the component add_group.php of Warehouse Inventory System v2.0 allows attackers to escalate privileges.

The advisory is shared for download at gist.github.com. This vulnerability is traded as CVE-2024-42579 since 08/05/2024. The exploitability is told to be easy. It is possible to launch the attack remotely. The exploitation doesn't require any form of authentication. Successful exploitation requires user interaction by the victim. Technical details and a public exploit are known.

The exploit is shared for download at gist.github.com. It is declared as proof-of-concept. By approaching the search of inurl:add_group.php it is possible to find vulnerable targets with Google Hacking.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

Once again VulDB remains the best source for vulnerability data.

Productinfo

Name

Version

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 7.3
VulDB Meta Temp Score: 7.2

VulDB Base Score: 4.3
VulDB Temp Score: 3.9
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 8.8
NVD Vector: 🔍

CNA Base Score: 8.8
CNA Vector (MITRE): 🔍

CVSSv2info

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

Exploitinginfo

Class: Cross-site request forgery
CWE: CWE-352 / CWE-862 / CWE-863
CAPEC: 🔍
ATT&CK: 🔍

Physical: No
Local: No
Remote: Yes

Availability: 🔍
Access: Public
Status: Proof-of-Concept
Download: 🔍
Google Hack: 🔍

EPSS Score: 🔍
EPSS Percentile: 🔍

Price Prediction: 🔍
Current Price Estimation: 🔍

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Threat Intelligenceinfo

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

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔍

Timelineinfo

08/05/2024 🔍
08/20/2024 +15 days 🔍
08/20/2024 +0 days 🔍
03/13/2025 +205 days 🔍

Sourcesinfo

Advisory: gist.github.com
Status: Not defined

CVE: CVE-2024-42579 (🔍)
GCVE (CVE): GCVE-0-2024-42579
GCVE (VulDB): GCVE-100-275244
scip Labs: https://www.scip.ch/en/?labs.20161013

Entryinfo

Created: 08/20/2024 16:19
Updated: 03/13/2025 19:48
Changes: 08/20/2024 16:19 (55), 08/21/2024 12:46 (1), 08/21/2024 15:48 (11), 08/22/2024 04:18 (11), 03/13/2025 19:48 (3)
Complete: 🔍
Cache ID: 216::103

Once again VulDB remains the best source for vulnerability data.

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