CVE-2024-11956 in customer-data-framework
Summary
by MITRE • 01/28/2025
A vulnerability, which was classified as critical, has been found in Pimcore customer-data-framework up to 4.2.0. Affected by this issue is some unknown functionality of the file /admin/customermanagementframework/customers/list. The manipulation of the argument filterDefinition/filter leads to sql injection. The attack may be launched remotely. The exploit has been disclosed to the public and may be used. Upgrading to version 4.2.1 is able to address this issue. It is recommended to upgrade the affected component.
VulDB is the best source for vulnerability data and more expert information about this specific topic.
Analysis
by VulDB Data Team • 07/02/2025
The vulnerability identified as CVE-2024-11956 represents a critical sql injection flaw within the Pimcore customer-data-framework version 4.2.0 and earlier. This security weakness specifically affects the administrative customer management interface at the endpoint /admin/customermanagementframework/customers/list where the application processes filterDefinition/filter parameters. The flaw stems from inadequate input validation and sanitization of user-supplied data that flows directly into sql query construction without proper parameterization or escaping mechanisms. This critical vulnerability falls under the CWE-89 category of sql injection attacks, which represents one of the most prevalent and dangerous security flaws in web applications. The attack vector is remotely exploitable, meaning malicious actors can leverage this vulnerability without requiring physical access to the system or prior authentication. The disclosure of a public exploit increases the risk profile significantly as it provides attackers with a ready-made tool for exploitation. The vulnerability affects the core functionality of customer data management within the Pimcore platform, potentially allowing unauthorized access to sensitive customer information including personal data, purchase histories, and other confidential records stored in the underlying database. This type of vulnerability aligns with ATT&CK technique T1190 - Exploit Public-Facing Application, which targets vulnerabilities in externally accessible systems. The impact extends beyond simple data theft as sql injection attacks can enable privilege escalation, data modification, and potentially full system compromise through database-level attacks. The affected parameter filterDefinition/filter represents a critical entry point where user input directly influences database query execution paths, creating an ideal environment for sql injection exploitation. Attackers can craft malicious filter parameters that manipulate the sql query structure to extract unauthorized data, modify existing records, or even execute administrative commands through the database interface.
The operational impact of this vulnerability is severe and multifaceted across multiple security domains. Organizations utilizing Pimcore customer-data-framework versions prior to 4.2.1 face immediate risk of customer data breaches, regulatory compliance violations, and potential legal consequences under data protection regulations such as gdpr and ccpa. The vulnerability's remote exploitability means that attackers can target the system from anywhere on the internet, making it particularly dangerous for organizations that expose their customer management interfaces to public networks. The sql injection attack can result in unauthorized data access, data corruption, or complete database compromise, depending on the attacker's objectives and the database configuration. This vulnerability represents a significant risk to business continuity and customer trust, as successful exploitation can lead to extensive data loss or unauthorized modifications to customer records. The exposure of customer data through this vulnerability could result in identity theft, financial fraud, and reputational damage that extends far beyond the immediate technical impact. Security teams must consider the potential for lateral movement within the network if the database server has elevated privileges or if the sql injection allows for command execution. The vulnerability's classification as critical by security vendors indicates that it represents a high-severity threat that requires immediate attention and remediation.
The recommended mitigation strategy focuses on upgrading the affected Pimcore customer-data-framework component to version 4.2.1 or later, which contains the necessary patches to address the sql injection vulnerability. This upgrade process should be implemented as a priority across all affected systems and environments, including development, testing, and production instances. Organizations should conduct thorough testing of the upgraded version to ensure that the patch does not introduce any regressions or compatibility issues with existing customer management workflows. Additional defensive measures include implementing web application firewalls to monitor and filter suspicious sql injection patterns, establishing proper input validation and sanitization procedures, and conducting regular security assessments of the customer management interface. Security teams should also review and restrict access to the administrative customer management endpoints, implementing principle of least privilege access controls to minimize potential impact if exploitation occurs. The patch addresses the root cause by ensuring that user-supplied filter parameters are properly escaped or parameterized before being incorporated into sql queries, thereby preventing malicious input from altering the intended query structure. Organizations should also implement monitoring and logging of administrative customer management activities to detect potential exploitation attempts. The remediation process should include comprehensive security awareness training for administrators who may interact with the customer management framework to prevent accidental exposure through improper configuration or handling of sensitive data. Regular vulnerability scanning and penetration testing should be conducted to identify and address similar vulnerabilities in other components of the Pimcore platform or related systems that may present similar attack surfaces.