CVE-2025-6503 is a SQL Injection vulnerability identified in version 1.0 of the code-projects Inventory Management System. The vulnerability arises from improper handling of the 'categoriesId' parameter in the /php_action/fetchSelectedCategories.php endpoint. An attacker can remotely manipulate this parameter to inject malicious SQL code, potentially allowing unauthorized access to or modification of the backend database. The vulnerability requires no authentication or user interaction, and can be exploited over the network (AV:N, AC:L, PR:N, UI:N). The CVSS 4.0 base score is 6.9 (medium severity), reflecting the ease of exploitation and the limited impact on confidentiality, integrity, and availability (VC:L, VI:L, VA:L). The vulnerability does not require privileges or user interaction, and the scope is unchanged, meaning the impact is confined to the vulnerable component. Although no public exploits are currently known in the wild, the disclosure of the vulnerability means attackers could develop exploits. The Inventory Management System is typically used by organizations to track and manage stock and related data, making the database a critical asset. Exploitation could lead to unauthorized data disclosure, data tampering, or disruption of inventory operations. The lack of available patches or mitigations from the vendor increases the risk for users of version 1.0. Given the nature of SQL Injection, attackers could escalate the impact by extracting sensitive business data or corrupting records, potentially affecting business continuity and compliance with data protection regulations.

For European organizations using the affected Inventory Management System version 1.0, this vulnerability poses a significant risk to the confidentiality and integrity of inventory and related business data. Unauthorized database access could lead to leakage of sensitive commercial information, including supplier details, stock levels, and pricing. Data integrity could be compromised by unauthorized modification or deletion of records, disrupting supply chain and operational processes. This could result in financial losses, reputational damage, and regulatory non-compliance, especially under GDPR where personal or sensitive data might be involved. Availability impact is limited but possible if attackers corrupt data or disrupt database queries. The medium CVSS score reflects that while exploitation is straightforward, the overall damage is somewhat contained. However, the lack of patches and the public disclosure increase the urgency for European organizations to act. Industries with critical inventory management needs, such as manufacturing, retail, and logistics, are particularly at risk. Additionally, organizations with interconnected systems relying on this inventory data could face cascading operational impacts.

1. Immediate mitigation should include implementing web application firewall (WAF) rules to detect and block malicious SQL injection payloads targeting the 'categoriesId' parameter in /php_action/fetchSelectedCategories.php. 2. Conduct thorough input validation and parameterized queries or prepared statements in the application code to prevent SQL injection. Since no official patch is currently available, organizations should review and modify the source code if accessible. 3. Restrict database user permissions to the minimum necessary to limit the impact of any injection attack. 4. Monitor database logs and application logs for unusual queries or access patterns indicative of exploitation attempts. 5. Isolate the Inventory Management System from public networks or restrict access via VPN or IP whitelisting to reduce exposure. 6. Prepare incident response plans specific to database compromise scenarios. 7. Engage with the vendor or community to obtain or develop patches and apply them promptly once available. 8. Perform regular security assessments and penetration testing focusing on injection vulnerabilities in all web-facing applications. 9. Educate developers and administrators on secure coding practices and the risks of SQL injection.