CVE-2025-22283: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') in Riyaz GetSocial
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') vulnerability in Riyaz GetSocial getsocial allows Reflected XSS.This issue affects GetSocial: from n/a through <= 2.0.1.
AI Analysis
Technical Summary
CVE-2025-22283 identifies a reflected Cross-site Scripting (XSS) vulnerability in the Riyaz GetSocial product, specifically affecting versions up to and including 2.0.1. The vulnerability stems from improper neutralization of user-supplied input during the generation of web pages, which allows attackers to inject malicious JavaScript code that is reflected back to the victim's browser. When a user interacts with a crafted URL or input, the malicious script executes in their browser context, potentially leading to session hijacking, credential theft, or unauthorized actions performed with the victim's privileges. GetSocial is a social engagement platform commonly embedded in websites to enhance user interaction and sharing capabilities. The absence of a CVSS score and official patches indicates this is a newly disclosed vulnerability with limited public exploitation data. However, reflected XSS vulnerabilities are generally easy to exploit and can have significant security implications, especially if the affected websites handle sensitive user data or authentication tokens. The vulnerability does not require prior authentication, increasing its risk profile. The lack of known exploits in the wild suggests proactive mitigation can prevent attacks. The technical root cause is insufficient input validation and output encoding in the web page generation process within GetSocial, which should be addressed by sanitizing inputs and applying context-aware encoding before rendering content to users.
Potential Impact
If exploited, this vulnerability can compromise the confidentiality and integrity of user data by enabling attackers to execute arbitrary scripts in the context of affected websites. This can lead to theft of session cookies, enabling account takeover, unauthorized actions on behalf of users, and distribution of malware or phishing content. The availability impact is generally low but could be indirectly affected if attackers use the vulnerability to deface websites or disrupt user interactions. Organizations integrating GetSocial into their web platforms risk reputational damage and loss of user trust if the vulnerability is exploited. Since the vulnerability does not require authentication and is reflected, it can be exploited by simply tricking users into clicking malicious links, increasing the attack surface. The lack of patches means organizations must rely on temporary mitigations until an official fix is released. Overall, the threat can affect a broad range of websites using GetSocial, potentially impacting millions of users globally.
Mitigation Recommendations
Organizations should immediately review their use of GetSocial and implement input validation and output encoding controls to neutralize potentially malicious input before rendering it in web pages. Employing Content Security Policy (CSP) headers can help mitigate the impact of XSS by restricting script execution sources. Web application firewalls (WAFs) should be configured to detect and block reflected XSS attack patterns targeting GetSocial endpoints. Until an official patch is available, consider disabling or removing GetSocial integrations on critical websites or limiting their exposure. Security teams should monitor for suspicious activity and educate users about the risks of clicking untrusted links. Developers should audit the GetSocial codebase for other input handling issues and prepare to apply vendor patches promptly once released. Regular security testing, including automated scanning and manual penetration testing focused on XSS, is recommended to identify and remediate similar vulnerabilities.
Affected Countries
United States, India, United Kingdom, Germany, Canada, Australia, France, Brazil, Japan, Netherlands
CVE-2025-22283: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') in Riyaz GetSocial
Description
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') vulnerability in Riyaz GetSocial getsocial allows Reflected XSS.This issue affects GetSocial: from n/a through <= 2.0.1.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2025-22283 identifies a reflected Cross-site Scripting (XSS) vulnerability in the Riyaz GetSocial product, specifically affecting versions up to and including 2.0.1. The vulnerability stems from improper neutralization of user-supplied input during the generation of web pages, which allows attackers to inject malicious JavaScript code that is reflected back to the victim's browser. When a user interacts with a crafted URL or input, the malicious script executes in their browser context, potentially leading to session hijacking, credential theft, or unauthorized actions performed with the victim's privileges. GetSocial is a social engagement platform commonly embedded in websites to enhance user interaction and sharing capabilities. The absence of a CVSS score and official patches indicates this is a newly disclosed vulnerability with limited public exploitation data. However, reflected XSS vulnerabilities are generally easy to exploit and can have significant security implications, especially if the affected websites handle sensitive user data or authentication tokens. The vulnerability does not require prior authentication, increasing its risk profile. The lack of known exploits in the wild suggests proactive mitigation can prevent attacks. The technical root cause is insufficient input validation and output encoding in the web page generation process within GetSocial, which should be addressed by sanitizing inputs and applying context-aware encoding before rendering content to users.
Potential Impact
If exploited, this vulnerability can compromise the confidentiality and integrity of user data by enabling attackers to execute arbitrary scripts in the context of affected websites. This can lead to theft of session cookies, enabling account takeover, unauthorized actions on behalf of users, and distribution of malware or phishing content. The availability impact is generally low but could be indirectly affected if attackers use the vulnerability to deface websites or disrupt user interactions. Organizations integrating GetSocial into their web platforms risk reputational damage and loss of user trust if the vulnerability is exploited. Since the vulnerability does not require authentication and is reflected, it can be exploited by simply tricking users into clicking malicious links, increasing the attack surface. The lack of patches means organizations must rely on temporary mitigations until an official fix is released. Overall, the threat can affect a broad range of websites using GetSocial, potentially impacting millions of users globally.
Mitigation Recommendations
Organizations should immediately review their use of GetSocial and implement input validation and output encoding controls to neutralize potentially malicious input before rendering it in web pages. Employing Content Security Policy (CSP) headers can help mitigate the impact of XSS by restricting script execution sources. Web application firewalls (WAFs) should be configured to detect and block reflected XSS attack patterns targeting GetSocial endpoints. Until an official patch is available, consider disabling or removing GetSocial integrations on critical websites or limiting their exposure. Security teams should monitor for suspicious activity and educate users about the risks of clicking untrusted links. Developers should audit the GetSocial codebase for other input handling issues and prepare to apply vendor patches promptly once released. Regular security testing, including automated scanning and manual penetration testing focused on XSS, is recommended to identify and remediate similar vulnerabilities.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- Patchstack
- Date Reserved
- 2025-01-03T13:15:43.300Z
- Cvss Version
- null
- State
- PUBLISHED
Threat ID: 69cd75d6e6bfc5ba1df07fbd
Added to database: 4/1/2026, 7:45:26 PM
Last enriched: 4/2/2026, 10:03:37 AM
Last updated: 4/4/2026, 8:19:56 AM
Views: 5
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