CVE-2022-31092 is a medium-severity SQL Injection vulnerability affecting Pimcore, an open-source Data & Experience Management Platform widely used for managing digital data and customer experiences. The vulnerability arises from improper neutralization of special elements in SQL commands (CWE-89) within Pimcore's listing classes, which developers use to query data. These listing classes provide functionality to order or group query results by one or more columns, which are expected to be automatically quoted to prevent injection attacks. However, in versions prior to 10.4.4, the quoting mechanism is flawed and does not properly escape or quote the input parameters. This creates a theoretical possibility for attackers to inject arbitrary SQL commands if developers pass unvalidated or unsanitized input to these listing methods, relying solely on Pimcore's auto-quoting feature. Exploiting this vulnerability could allow an attacker to manipulate database queries, potentially leading to unauthorized data access, data modification, or even deletion. The issue was addressed and fixed in Pimcore version 10.4.4. No known exploits have been reported in the wild, and no workarounds exist other than upgrading or applying the patch manually. The vulnerability requires that the application uses vulnerable Pimcore versions and that developers pass untrusted input without proper validation, which means exploitation depends on the specific implementation of the affected application.

For European organizations using Pimcore versions prior to 10.4.4, this vulnerability poses a risk of unauthorized access to sensitive data stored within their Pimcore-managed databases. Given Pimcore's role in managing customer data, product information, and digital assets, successful exploitation could compromise confidentiality by exposing personal or proprietary data. Integrity could be impacted if attackers modify or delete data via injected SQL commands, potentially disrupting business operations or corrupting critical datasets. Availability risks exist if injected queries cause database errors or crashes. The impact is heightened for organizations in sectors with strict data protection regulations such as GDPR, where data breaches can lead to significant legal and financial penalties. Since exploitation requires that developers use vulnerable listing classes with unvalidated input, the risk varies depending on the security practices of the deploying organization. However, the widespread use of Pimcore across European digital agencies, e-commerce, and media companies means that a significant number of organizations could be affected if they have not updated to the patched version. The absence of known exploits reduces immediate threat but does not eliminate the risk, especially as attackers often target known vulnerabilities in popular platforms.

1. Immediate upgrade to Pimcore version 10.4.4 or later is the primary and most effective mitigation step to eliminate the vulnerability. 2. For organizations unable to upgrade immediately, manually apply the security patch provided by Pimcore addressing this issue. 3. Conduct a thorough code review of all Pimcore listing class usages to ensure that no untrusted input is passed directly without proper validation or sanitization. 4. Implement strict input validation and sanitization on all user-supplied data before it reaches the database query layer, especially for parameters used in ordering or grouping queries. 5. Employ parameterized queries or prepared statements where possible to prevent SQL injection risks. 6. Monitor database logs and application logs for unusual query patterns or errors that may indicate attempted exploitation. 7. Restrict database user privileges to the minimum necessary to limit the impact of any potential injection. 8. Incorporate Web Application Firewalls (WAFs) with SQL injection detection rules tailored to Pimcore query patterns to provide an additional layer of defense. 9. Educate developers on secure coding practices related to database queries and the risks of relying on framework auto-quoting features without validation.