CVE-2025-64070 identifies a Cross Site Scripting (XSS) vulnerability in the Sourcecodester Student Grades Management System version 1.0. The vulnerability exists in the Add New Subject Description field, where user-supplied input is not properly sanitized or encoded before being rendered in the web application. This allows an attacker to inject malicious JavaScript code that executes in the browsers of users who view the affected page. The vulnerability does not require authentication, meaning any unauthenticated attacker can craft a malicious payload and trick users into executing it, typically through social engineering or phishing. The lack of a CVSS score suggests this is a newly published vulnerability with limited public information and no available patches at the time of reporting. The absence of known exploits in the wild indicates that active exploitation has not yet been observed, but the nature of XSS vulnerabilities makes them a common target for attackers seeking to steal session cookies, perform actions on behalf of users, or deface web content. The vulnerability impacts confidentiality by potentially exposing sensitive user data and session tokens, and integrity by allowing unauthorized script execution. Availability impact is minimal but could be affected if the injected scripts disrupt normal application functionality. The vulnerability affects all deployments of Sourcecodester Student Grades Management System v1.0 that have not implemented custom input validation or output encoding. Since this is an educational management system, the primary targets are educational institutions and administrators managing student grades and subjects. The technical details do not provide a patch or mitigation guidance, so organizations must implement input validation, output encoding, and Content Security Policy (CSP) headers to mitigate risk. Monitoring logs for suspicious input patterns and educating users about phishing risks are also recommended.

For European organizations, particularly educational institutions using Sourcecodester Student Grades Management System v1.0, this XSS vulnerability could lead to unauthorized disclosure of sensitive student and staff information, session hijacking, and unauthorized actions performed on behalf of users. The breach of confidentiality could violate GDPR requirements, leading to regulatory penalties and reputational damage. Integrity of data could be compromised if attackers manipulate displayed content or inject malicious scripts that alter user interactions. Although availability impact is limited, persistent exploitation could degrade user trust and system usability. The vulnerability could also be leveraged as a foothold for further attacks within the network if combined with other vulnerabilities. Given the educational sector's critical role and the sensitivity of student data, the impact is significant. Organizations lacking timely mitigation may face increased risk of targeted phishing campaigns exploiting this vulnerability to gain access to internal systems or sensitive data.

To mitigate CVE-2025-64070, organizations should immediately implement strict input validation on the Add New Subject Description field to reject or sanitize any HTML or script content. Employ output encoding techniques such as HTML entity encoding to ensure that user input is safely rendered without executing as code. Deploy Content Security Policy (CSP) headers to restrict the execution of unauthorized scripts and reduce the impact of any injected code. Regularly audit and update the Student Grades Management System to the latest secure versions or apply vendor patches once available. Conduct security awareness training for users to recognize phishing attempts that could exploit this vulnerability. Monitor web server and application logs for unusual input patterns or error messages indicative of attempted XSS attacks. Consider implementing web application firewalls (WAF) with rules to detect and block XSS payloads targeting the affected field. Finally, segregate the affected system within the network to limit lateral movement if exploitation occurs.