CVE-2002-1006 in Betsie
Summary
by MITRE
Cross-site scripting (XSS) vulnerability in BBC Education Text to Speech Internet Enhancer (Betsie) 1.5.11 and earlier allows remote attackers to execute arbitrary web script via parserl.pl.
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Analysis
by VulDB Data Team • 09/10/2025
The vulnerability described in CVE-2002-1006 represents a classic cross-site scripting flaw within the BBC Education Text to Speech Internet Enhancer version 1.5.11 and earlier. This security weakness specifically affects the parserl.pl component of the software, which serves as a critical parsing mechanism for processing text content. The vulnerability stems from inadequate input validation and sanitization within the web application's processing pipeline, creating an exploitable condition where malicious scripts can be injected and executed within the context of other users' browsers.
The technical implementation of this XSS vulnerability occurs when the parserl.pl script fails to properly sanitize user-supplied input before incorporating it into dynamically generated web content. This allows an attacker to inject malicious javascript code through the text processing interface, which then gets executed whenever other users view the affected content. The flaw operates under CWE-79 which specifically addresses Cross-Site Scripting vulnerabilities, where insufficient validation of user inputs leads to the execution of unintended code within the victim's browser context. The vulnerability exists at the application layer where the software processes and renders user-generated content without proper security controls to prevent script injection attacks.
The operational impact of this vulnerability extends beyond simple script execution, as it enables attackers to perform various malicious activities including session hijacking, credential theft, data exfiltration, and redirection to malicious websites. Users of the BBC Education Text to Speech Internet Enhancer who interact with content processed through the vulnerable parserl.pl script become potential victims of these attacks, particularly in educational environments where multiple users may access shared content. The vulnerability affects the integrity and confidentiality of user data, potentially compromising the security of entire educational systems that rely on this technology for text-to-speech functionality.
Mitigation strategies for this vulnerability should focus on implementing comprehensive input validation and output encoding mechanisms throughout the application's processing pipeline. The primary remediation involves updating the parserl.pl script to sanitize all user inputs before processing, implementing proper HTML encoding for dynamic content generation, and applying the principle of least privilege in script execution. Organizations should consider implementing Content Security Policies to prevent unauthorized script execution, while also ensuring that all affected systems receive immediate patch updates. The remediation aligns with ATT&CK technique T1566 which addresses social engineering through malicious content delivery, emphasizing the need for robust web application security controls to prevent such exploitation vectors from compromising user sessions and data integrity.