CVE-2025-41059 in CMF
Summary
by MITRE • 09/04/2025
A vulnerability has been discovered in appRain CMF version 4.0.5, consisting of a stored authenticated XSS due to a lack of proper validation of user input, through the 'data[Addon][layouts]' and 'data[Addon][layouts_except]' parameters in /apprain/developer/addons/update/tablesorter.
Be aware that VulDB is the high quality source for vulnerability data.
Analysis
by VulDB Data Team • 09/04/2025
The vulnerability identified as CVE-2025-41059 represents a critical stored cross-site scripting flaw within the appRain Content Management Framework version 4.0.5. This security weakness specifically manifests in the developer section of the application where administrators can manage addons through the tablesorter functionality. The flaw stems from insufficient input validation mechanisms that fail to properly sanitize user-supplied data before processing and storage within the application's database. Attackers with authenticated access can exploit this vulnerability by injecting malicious JavaScript code through the designated parameters, which then gets executed whenever the affected page is accessed by other users.
The technical implementation of this vulnerability occurs within the /apprain/developer/addons/update/tablesorter endpoint where the application accepts user input through the 'data[Addon][layouts]' and 'data[Addon][layouts_except]' parameters. These parameters are intended to manage addon layouts and exceptions but lack proper sanitization checks that would normally be implemented to prevent malicious code injection. When an authenticated user submits data containing script tags or other malicious payloads through these parameters, the application stores this content without adequate validation, creating a persistent XSS vector that can affect any user who views the affected content. This stored nature of the vulnerability means that the malicious code remains active in the database until manually removed, making it particularly dangerous as it can persist across multiple sessions and user interactions.
The operational impact of this vulnerability extends beyond simple script execution as it provides attackers with the ability to escalate privileges and potentially gain unauthorized access to sensitive system information. An attacker could craft malicious payloads that steal session cookies, redirect users to phishing sites, or even execute commands on the server if additional vulnerabilities exist within the application's architecture. The stored nature of the XSS means that victims do not need to be actively targeted during the injection phase, as the malicious code will execute automatically whenever the vulnerable page is rendered, creating a continuous threat vector. This vulnerability particularly affects administrators and users with developer privileges who regularly interact with the addon management system, making it a significant concern for organizations relying on this content management framework for their web applications.
Organizations should implement immediate mitigations including input validation and sanitization measures that specifically target the affected parameters within the tablesorter endpoint. The recommended approach involves implementing strict content validation that removes or encodes potentially dangerous characters and script tags from user input before storage. Additionally, implementing proper output encoding when displaying stored data can prevent malicious scripts from executing even if input validation fails. Security teams should also consider implementing web application firewalls that can detect and block suspicious payloads targeting these specific parameters. The vulnerability aligns with CWE-79 which classifies cross-site scripting as a critical weakness in web applications, and maps to ATT&CK technique T1566.001 which covers social engineering through phishing. Regular security assessments and input validation testing should be performed to ensure that similar vulnerabilities are not present in other parts of the application, as this type of flaw often indicates broader issues with data sanitization practices within the codebase.