CVE-2025-65368 identifies a Cross Site Scripting (XSS) vulnerability in SparkyFitness version 0.15.8.2, a fitness application platform. The vulnerability stems from inadequate sanitization of both user-supplied input and outputs generated by integrated large language models (LLMs). This dual vector increases the attack surface, as malicious actors can craft inputs or manipulate LLM outputs to inject executable scripts into the web interface. When a victim user interacts with the compromised content, the injected scripts can execute in their browser context, potentially leading to session hijacking, theft of sensitive data, or unauthorized actions performed on behalf of the user. The vulnerability has a CVSS 3.1 base score of 6.1, reflecting medium severity, with an attack vector of network (remote exploitation), low attack complexity, no privileges required, but requiring user interaction. The scope is changed (S:C), indicating that exploitation affects components beyond the vulnerable code itself. Confidentiality and integrity impacts are low, and availability is unaffected. No patches or known exploits are currently available, but the presence of LLM output as an injection vector is notable, as it introduces novel challenges in sanitization. This vulnerability is categorized under CWE-79, the common weakness enumeration for XSS. The vulnerability was reserved in November 2025 and published in January 2026, indicating recent discovery and disclosure.

For European organizations, the impact of CVE-2025-65368 can be significant, especially for those relying on SparkyFitness for employee wellness programs or customer engagement. Successful exploitation could lead to unauthorized access to user sessions, exposure of personal or health-related data, and manipulation of displayed content, undermining user trust and potentially violating GDPR data protection requirements. While availability is not impacted, the integrity and confidentiality of user data and interactions are at risk. Attackers could leverage this vulnerability to conduct phishing campaigns, spread malware, or escalate attacks within corporate networks. The reliance on LLM outputs as an injection vector also raises concerns about the security of AI-generated content in web applications. European organizations with high user interaction on such platforms face increased risk, and reputational damage could result from breaches stemming from this vulnerability.

To mitigate CVE-2025-65368, organizations should implement strict input validation and output encoding on all user-supplied data and LLM-generated content before rendering it in the browser. Employing Content Security Policy (CSP) headers can help restrict script execution and reduce the impact of injected scripts. Developers should sanitize or escape all dynamic content, especially from AI outputs, using well-established libraries designed for XSS prevention. Monitoring and logging user interactions can help detect exploitation attempts early. Until official patches are released, consider disabling or limiting features that incorporate LLM outputs in web interfaces. Conduct security code reviews focusing on AI integration points and perform penetration testing simulating XSS attacks. Educate users about the risks of interacting with suspicious content and maintain updated web application firewalls (WAFs) with rules targeting XSS patterns. Finally, track vendor advisories for patches and apply them promptly once available.