CVE-2012-5341 in StatIt
Summary
by MITRE
Multiple cross-site scripting (XSS) vulnerabilities in statistik.php in Otterware StatIt 4 allow remote attackers to inject arbitrary web script or HTML via the (1) action parameter, (2) show parameter in a stat_tld action, or (3) order parameter in a stat_abfragen action.
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Analysis
by VulDB Data Team • 04/25/2025
The vulnerability identified as CVE-2012-5341 represents a critical cross-site scripting flaw in Otterware StatIt 4's statistik.php component, which exposes users to significant web application security risks. This vulnerability falls under the CWE-79 category of Cross-Site Scripting, specifically targeting the application's input validation mechanisms that fail to properly sanitize user-supplied data. The flaw exists in the statistical reporting module where the application directly incorporates user-provided parameters into web responses without adequate sanitization or encoding measures. Attackers can exploit this vulnerability through three distinct parameter injection points that correspond to different functional areas of the statistical reporting system.
The technical exploitation occurs when remote attackers manipulate the action parameter, the show parameter within the stat_tld action, or the order parameter within the stat_abfragen action. These parameters are processed by the application without proper input validation, allowing malicious payloads to be executed within the context of legitimate user sessions. When users view pages containing the injected scripts, the malicious code executes in their browsers, potentially leading to session hijacking, credential theft, or unauthorized actions performed on behalf of the victim. The vulnerability's impact is amplified because it affects core statistical functionality that likely serves multiple users within an organization, making it a prime target for widespread exploitation.
The operational impact of this vulnerability extends beyond simple script execution, as it can enable attackers to perform sophisticated attacks such as cookie theft through session hijacking techniques, which aligns with ATT&CK technique T1539 for "Steal Web Session Cookie". Additionally, the vulnerability could facilitate more advanced attacks including phishing, data exfiltration, or even privilege escalation within the application's context. Organizations relying on Otterware StatIt 4 for statistical analysis and reporting would face significant risks to their web application security posture, potentially compromising sensitive data that the application processes and displays.
Mitigation strategies should focus on implementing comprehensive input validation and output encoding measures across all user-supplied parameters. The recommended approach includes sanitizing all input through proper validation libraries, implementing context-specific output encoding for HTML, JavaScript, and URL contexts, and applying the principle of least privilege to limit the impact of potential exploitation. Organizations should also consider implementing web application firewalls to detect and block suspicious parameter patterns, while ensuring that all web applications undergo regular security assessments to identify similar vulnerabilities. The vulnerability demonstrates the critical importance of input validation in web applications and serves as a reminder of the persistent threat that XSS vulnerabilities pose to modern web environments, particularly in statistical and reporting applications that process user data.