CVE-2025-8221 is a cross-site scripting (XSS) vulnerability identified in the JPACookieShop 蛋糕商城JPA版 e-commerce platform developed by jerryshensjf. The vulnerability exists in the goodsSearch function within the GoodsCustController.java file. Specifically, the issue arises from improper sanitization or validation of the 'keyword' parameter, which is manipulated by an attacker to inject malicious scripts. This vulnerability allows an attacker to execute arbitrary JavaScript code in the context of the victim's browser when they access a crafted URL or interact with the affected search functionality. The attack can be launched remotely without requiring authentication, and user interaction is necessary to trigger the malicious script execution. The product uses a rolling release model, which complicates precise version tracking, but the affected version is identified by the commit hash 24a15c02b4f75042c9f7f615a3fed2ec1cefb999. The CVSS 4.0 base score is 5.3, indicating a medium severity level. The vector indicates network attack vector, low attack complexity, no privileges or user interaction required for the attack initiation, but user interaction is needed to trigger the XSS payload. The vulnerability impacts the confidentiality and integrity of user data by enabling session hijacking, credential theft, or redirection to malicious sites, but does not directly affect system availability. No public exploit is currently known to be actively used in the wild, but the exploit details have been disclosed publicly, increasing the risk of exploitation. No official patches or updates have been linked, likely due to the continuous delivery model of the software. Organizations using this platform should consider this vulnerability a moderate risk that could facilitate further attacks such as phishing or account compromise.

For European organizations using the JPACookieShop 蛋糕商城JPA版 platform, this XSS vulnerability poses a tangible risk to customer data confidentiality and trust. Exploitation could lead to session hijacking, theft of personal information, or injection of malicious content that damages brand reputation. Given the e-commerce nature of the product, attackers could leverage this vulnerability to conduct fraudulent transactions or steal payment information indirectly through social engineering. The medium severity score reflects that while the vulnerability does not allow direct system compromise or denial of service, it can be a stepping stone for more sophisticated attacks. European data protection regulations such as GDPR impose strict requirements on protecting personal data; a successful attack exploiting this vulnerability could lead to regulatory penalties and loss of customer confidence. Furthermore, the lack of a formal patch and the rolling release model may delay remediation, increasing exposure time. Organizations relying on this software must assess their exposure and implement compensating controls to mitigate risks until an official fix is available.

1. Implement strict input validation and output encoding on the 'keyword' parameter in the goodsSearch function to neutralize malicious scripts. Use established libraries or frameworks that automatically handle XSS prevention. 2. Employ Content Security Policy (CSP) headers to restrict the execution of unauthorized scripts in browsers, limiting the impact of any injected code. 3. Conduct regular security code reviews and penetration testing focused on user input handling, especially in search and form functionalities. 4. Monitor web application logs for unusual or suspicious requests targeting the goodsSearch endpoint to detect potential exploitation attempts. 5. Educate users and administrators about the risks of XSS and encourage cautious behavior regarding suspicious links or inputs. 6. If possible, isolate or sandbox the affected component to limit the scope of any successful XSS attack. 7. Engage with the vendor or development team to prioritize a patch release and apply updates promptly once available. 8. Consider deploying Web Application Firewalls (WAFs) with custom rules to detect and block common XSS attack patterns targeting this parameter.