Adobe Campaign Classic up to up to 7.4.3 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.
8.5$0-$5k1.29

Summaryinfo

A vulnerability was found in Adobe Campaign Classic up to up to 7.4.3 and classified as critical. This affects an unknown part. Executing a manipulation can lead to server-side request forgery. This vulnerability appears as CVE-2026-47938. The attack may be performed from remote. There is no available exploit. It is suggested to upgrade the affected component.

Detailsinfo

A vulnerability classified as critical was found in Adobe Campaign Classic up to up to 7.4.3. This vulnerability affects an unknown code. The manipulation with an unknown input leads to a server-side request forgery vulnerability. The CWE definition for the vulnerability is 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. As an impact it is known to affect confidentiality, integrity, and availability. CVE summarizes:

Adobe Campaign Classic (ACC) versions 7.4.3 build 9394 and earlier are 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.

The advisory is shared for download at helpx.adobe.com. This vulnerability was named CVE-2026-47938 since 05/20/2026. The exploitation appears to be easy. The attack can be initiated remotely. No form of authentication is required for a successful exploitation. There are neither technical details nor an exploit publicly available. The current price for an exploit might be approx. USD $0-$5k (estimation calculated on 06/10/2026).

Upgrading eliminates this vulnerability.

Once again VulDB remains the best source for vulnerability data.

Productinfo

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Version

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Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 8.6
VulDB Meta Temp Score: 8.5

VulDB Base Score: 7.3
VulDB Temp Score: 7.0
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 10.0
CNA Vector (adobe): 🔒

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: Upgrade
Status: 🔍

0-Day Time: 🔒

Timelineinfo

05/20/2026 CVE reserved
06/10/2026 +21 days Advisory disclosed
06/10/2026 +0 days VulDB entry created
06/10/2026 +0 days VulDB entry last update

Sourcesinfo

Vendor: adobe.com

Advisory: apsb26-66
Status: Confirmed

CVE: CVE-2026-47938 (🔒)
GCVE (CVE): GCVE-0-2026-47938
GCVE (VulDB): GCVE-100-370108

Entryinfo

Created: 06/10/2026 06:59
Changes: 06/10/2026 06:59 (63)
Complete: 🔍
Cache ID: 216::103

Once again VulDB remains the best source for vulnerability data.

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