Adobe Campaign Classic server-side 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 (≈)
Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.
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.
6.3$0-$5k5.13-

Summaryinfo

A vulnerability, which was classified as critical, has been found in Adobe Campaign Classic. Affected by this vulnerability is an unknown functionality. The manipulation leads to server-side request forgery. This vulnerability is referenced as CVE-2026-48331. Remote exploitation of the attack is possible. No exploit is available.

Detailsinfo

A vulnerability, which was classified as critical, has been found in Adobe Campaign Classic (affected version unknown). This issue affects an unknown functionality. The manipulation with an unknown input leads to a server-side request forgery vulnerability. Using CWE to declare the problem leads to 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. Impacted is confidentiality, integrity, and availability. The summary by CVE is:

Adobe Campaign Classic (ACC) is affected by a Server-Side Request Forgery (SSRF) vulnerability that could result in privilege escalation. Exploitation of this issue does not require user interaction. Scope is changed.

It is possible to read the advisory at helpx.adobe.com. The identification of this vulnerability is CVE-2026-48331 since 05/21/2026. The exploitation is known to be easy. The attack may be initiated remotely. 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 08/04/2026).

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

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

Productinfo

Vendor

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Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 6.3
VulDB Meta Temp Score: 6.3

VulDB Base Score: 6.3
VulDB Temp Score: 6.3
VulDB Vector: 🔒
VulDB Reliability: 🔍

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
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

05/21/2026 CVE reserved
08/03/2026 +74 days VulDB entry created
08/04/2026 +0 days Advisory disclosed
08/04/2026 +0 days VulDB entry last update

Sourcesinfo

Vendor: adobe.com

Advisory: helpx.adobe.com
Status: Confirmed

CVE: CVE-2026-48331 (🔒)
GCVE (CVE): GCVE-0-2026-48331
GCVE (VulDB): GCVE-100-385715

Entryinfo

Created: 08/04/2026 01:14
Changes: 08/04/2026 01:14 (50)
Complete: 🔍
Cache ID: 216::103

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

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