ObjectPlanet Opinio 7.26 rev12562 Import server-side request forgery

CVSS Meta Temp Score
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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.
6.6$0-$5k0.00

Summaryinfo

A vulnerability identified as critical has been detected in ObjectPlanet Opinio 7.26 rev12562. This impacts an unknown function of the component Import Handler. Performing a manipulation results in server-side request forgery. This vulnerability is known as CVE-2025-13872. Remote exploitation of the attack is possible. No exploit is available.

Detailsinfo

A vulnerability classified as critical has been found in ObjectPlanet Opinio 7.26 rev12562. This affects some unknown functionality of the component Import Handler. The manipulation with an unknown input leads to a server-side request forgery vulnerability. CWE is classifying the issue as CWE-918. The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:

Blind Server-Side Request Forgery (SSRF) in the survey-import feature of ObjectPlanet Opinio 7.26 rev12562 on Web-based platforms allows an attacker to force the server to perform HTTP GET requests via crafted import requests to an arbitrary destination.

The weakness was published by Dominique Righetto. It is possible to read the advisory at objectplanet.com. This vulnerability is uniquely identified as CVE-2025-13872 since 12/02/2025. The exploitability is told to be difficult. It is possible to initiate the attack remotely. The exploitation requires an enhanced level of successful authentication. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 12/05/2025).

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

The vulnerability is also documented in the vulnerability database at EUVD (EUVD-2025-200216). Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Vendor

Name

Version

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒

CVSSv3info

VulDB Meta Base Score: 6.6
VulDB Meta Temp Score: 6.6

VulDB Base Score: 4.1
VulDB Temp Score: 4.1
VulDB Vector: 🔒
VulDB Reliability: 🔍

NVD Base Score: 9.1
NVD Vector: 🔒

CVSSv2info

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

Exploitinginfo

Class: Server-side request forgery
CWE: CWE-918
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: no mitigation known
Status: 🔍

0-Day Time: 🔒

Timelineinfo

12/02/2025 Advisory disclosed
12/02/2025 +0 days CVE reserved
12/02/2025 +0 days VulDB entry created
12/05/2025 +3 days VulDB entry last update

Sourcesinfo

Advisory: objectplanet.com
Researcher: Dominique Righetto
Status: Confirmed

CVE: CVE-2025-13872 (🔒)
GCVE (CVE): GCVE-0-2025-13872
GCVE (VulDB): GCVE-100-334035
EUVD: 🔒

Entryinfo

Created: 12/02/2025 11:09
Updated: 12/05/2025 20:09
Changes: 12/02/2025 11:09 (66), 12/04/2025 21:43 (1), 12/05/2025 20:09 (11)
Complete: 🔍
Cache ID: 216::103

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

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