CVE-2015-2872 in Deep Discovery
Summary
by MITRE
Multiple cross-site scripting (XSS) vulnerabilities in Trend Micro Deep Discovery Inspector (DDI) on Deep Discovery Threat appliances with software before 3.5.1477, 3.6.x before 3.6.1217, 3.7.x before 3.7.1248, 3.8.x before 3.8.1263, and other versions allow remote attackers to inject arbitrary web script or HTML via (1) crafted input to index.php that is processed by certain Internet Explorer 7 configurations or (2) crafted input to the widget feature.
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Analysis
by VulDB Data Team • 12/22/2024
The vulnerability identified as CVE-2015-2872 represents a critical cross-site scripting flaw affecting Trend Micro Deep Discovery Inspector appliances that operate with software versions prior to specific patch levels. This vulnerability exists within the Deep Discovery Threat appliances and specifically targets the index.php script and widget functionality, creating potential entry points for malicious actors to execute unauthorized code within the context of affected systems. The flaw manifests when the system processes user-supplied input without proper sanitization, allowing attackers to inject malicious scripts that can be executed by other users who access the affected web interface.
The technical nature of this vulnerability stems from inadequate input validation and output encoding mechanisms within the web application layer of the Trend Micro DDI appliances. When crafted input is submitted to index.php, particularly when processed through Internet Explorer 7 configurations, the system fails to properly escape or filter malicious content, enabling script execution. Additionally, the widget feature presents another attack vector where malicious input can be injected and subsequently rendered within the web interface. This vulnerability aligns with CWE-79, which specifically addresses cross-site scripting flaws in web applications, and represents a classic case of improper neutralization of input during web application development. The vulnerability is particularly concerning because it affects multiple version branches including 3.5, 3.6, 3.7, and 3.8, indicating a widespread issue across the product line.
The operational impact of this vulnerability is significant as it provides remote attackers with the capability to execute arbitrary web scripts or HTML code within the context of authenticated users' browsers. This could enable attackers to steal session cookies, perform unauthorized actions on behalf of users, redirect victims to malicious sites, or extract sensitive information from the appliance's administrative interface. The vulnerability affects the security posture of organizations relying on Trend Micro DDI appliances for threat detection and monitoring, as it could be exploited to compromise the integrity of the security infrastructure itself. Attackers could leverage this vulnerability to establish persistent access to the appliance, potentially gaining visibility into network traffic analysis capabilities and undermining the security monitoring functions that the appliance is designed to provide.
Organizations should immediately implement mitigations including applying the vendor-supplied patches for all affected versions of Trend Micro Deep Discovery Inspector software, specifically upgrading to versions 3.5.1477, 3.6.1217, 3.7.1248, and 3.8.1263 or later. Network segmentation and access controls should be enforced to limit exposure of the appliance to untrusted networks, while web application firewalls can provide additional protection layers. Regular security assessments and monitoring of the appliance's web interface should be conducted to detect any anomalous behavior or unauthorized access attempts. The vulnerability also highlights the importance of implementing defense-in-depth strategies that include regular patch management, input validation controls, and security awareness training for administrators to prevent exploitation of similar vulnerabilities in other systems. This vulnerability demonstrates the critical need for proper web application security practices and the potential consequences when input validation mechanisms fail to properly sanitize user-supplied data, particularly in security-critical applications that handle sensitive network monitoring information.