CVE-2025-31992 in MaxAI Assistant
Summary
by MITRE • 10/12/2025
HCL Unica MaxAI Assistant is susceptible to a HTML injection vulnerability. An attacker could insert special characters that are processed client-side in the context of the user's session.
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Analysis
by VulDB Data Team • 10/13/2025
The vulnerability identified as CVE-2025-31992 affects HCL Unica MaxAI Assistant, a platform designed for enterprise artificial intelligence assistance and analytics. This HTML injection vulnerability represents a critical security flaw that undermines the integrity of client-side processing within the application's user session context. The vulnerability stems from insufficient input validation and sanitization mechanisms that fail to properly escape or filter special characters entered by users, allowing malicious payloads to be executed within the browser environment of authenticated users. The affected system processes user inputs without adequate protection against cross-site scripting attacks, creating a pathway for attackers to manipulate the application's behavior and potentially access sensitive user data or session information. This type of vulnerability directly violates security principles outlined in the OWASP Top Ten, specifically addressing the risks associated with insecure input handling and client-side code execution.
The technical exploitation of this vulnerability occurs when an attacker crafts malicious input containing HTML or JavaScript code that gets rendered within the user's browser session. When the application processes this input without proper sanitization, the injected code executes in the context of the victim's session, potentially allowing for session hijacking, data theft, or further exploitation of the user's privileges. The vulnerability operates at the application layer, specifically targeting the client-side rendering mechanisms that handle user-provided content. Attackers can leverage this weakness to inject malicious scripts that can steal cookies, redirect users to malicious sites, or perform actions on behalf of authenticated users. The impact is particularly severe because the vulnerability affects the MaxAI Assistant platform's core functionality, where users may enter sensitive business data or perform administrative tasks that could be compromised through this injection vector.
The operational impact of CVE-2025-31992 extends beyond simple data theft, as it can enable attackers to establish persistent access to enterprise environments through compromised user sessions. Organizations utilizing HCL Unica MaxAI Assistant may experience unauthorized access to confidential business intelligence, customer data, or proprietary information that flows through the platform. The vulnerability also poses risks to business continuity and regulatory compliance, as unauthorized access to enterprise systems can result in significant financial losses and reputational damage. Security teams must consider the potential for privilege escalation if the application grants administrative capabilities to users, as an attacker could leverage this vulnerability to gain elevated access rights. The vulnerability's impact is amplified in enterprise environments where users may have extensive access permissions within the MaxAI platform, potentially allowing attackers to move laterally through the organization's digital infrastructure.
Mitigation strategies for CVE-2025-31992 should focus on implementing comprehensive input validation and output encoding mechanisms throughout the application's processing pipeline. Organizations must ensure that all user inputs are properly sanitized and that special characters are appropriately escaped before being rendered in client-side contexts. The implementation of Content Security Policy headers can provide additional protection against script execution, while regular security assessments and code reviews should be conducted to identify similar vulnerabilities. Organizations should also implement proper session management controls and consider deploying web application firewalls to detect and block malicious payloads. According to CWE guidelines, this vulnerability maps to CWE-79 which addresses cross-site scripting flaws, and aligns with ATT&CK technique T1566 related to spearphishing with malicious attachments or links. Regular patch management procedures should be established, and security awareness training for developers should emphasize secure coding practices to prevent similar injection vulnerabilities in future releases. The vulnerability underscores the critical importance of maintaining robust security controls in AI assistant platforms that handle sensitive enterprise data and user interactions.