CVE-2025-13981 in AI
Summary
by MITRE • 01/28/2026
Improper Neutralization of Input During Web Page Generation ("Cross-site Scripting") vulnerability in Drupal AI (Artificial Intelligence) allows Cross-Site Scripting (XSS).This issue affects AI (Artificial Intelligence): from 0.0.0 before 1.0.7, from 1.1.0 before 1.1.7, from 1.2.0 before 1.2.4.
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Analysis
by VulDB Data Team • 02/19/2026
The vulnerability CVE-2025-13981 represents a critical cross-site scripting flaw within the Drupal AI module, specifically targeting the improper neutralization of input during web page generation processes. This vulnerability falls under the well-established CWE-79 category for cross-site scripting, where malicious input is not adequately sanitized before being rendered in web pages, creating opportunities for attackers to inject malicious scripts into web applications. The Drupal AI module, designed to provide artificial intelligence capabilities within the Drupal content management system, becomes a vector for client-side attacks when user-provided data is not properly validated or escaped before being incorporated into dynamic web content. The affected versions span multiple release branches, indicating a widespread issue that impacts various deployment scenarios from version 0.0.0 through 1.0.6, 1.1.0 through 1.1.6, and 1.2.0 through 1.2.3, suggesting the vulnerability has persisted across multiple minor releases and potentially affected a broad user base.
The technical flaw manifests when the Drupal AI module processes user input or data from external sources and fails to implement proper output encoding or sanitization mechanisms before incorporating this data into HTML content generation. This allows attackers to inject malicious JavaScript code, HTML tags, or other potentially harmful content that executes in the context of other users' browsers. The vulnerability is particularly concerning because it operates at the web page generation layer, meaning that any data processed by the AI module and subsequently rendered to users could serve as an attack vector. The attack surface expands when considering that AI modules often process natural language inputs, API responses, or user-generated content that may contain untrusted data, making the sanitization process critical for maintaining application security.
Operationally, this XSS vulnerability poses significant risks to Drupal installations using the AI module, as it enables attackers to perform various malicious activities including session hijacking, credential theft, defacement of content, redirection to malicious sites, and potential privilege escalation within the application context. The impact extends beyond simple data theft to include potential compromise of the entire Drupal installation, especially when combined with other vulnerabilities or when the AI module processes sensitive information from authenticated users. Attackers could exploit this vulnerability to execute scripts in the context of authenticated users, potentially gaining access to administrative functions or sensitive data processing capabilities that the AI module might provide. The vulnerability's presence across multiple versions suggests that organizations implementing Drupal AI solutions may have been exposed to risk for extended periods, potentially allowing attackers to establish persistent footholds within their environments.
Mitigation strategies for CVE-2025-13981 should prioritize immediate remediation through the application of available patches or updates to versions 1.0.7, 1.1.7, and 1.2.4, which contain the necessary fixes for the XSS vulnerability. Organizations should implement comprehensive input validation and output encoding mechanisms throughout their Drupal installations, particularly focusing on the AI module's data processing pipelines. Security measures should include the implementation of Content Security Policy headers, proper HTML escaping of all dynamic content, and regular security audits of user input handling within the application. Additionally, administrators should consider implementing web application firewalls and monitoring systems to detect potential exploitation attempts, while also ensuring that all users are educated about the risks of interacting with untrusted content within the Drupal environment. The vulnerability's classification under ATT&CK technique T1059.001 for command and scripting interpreter and T1566 for phishing demonstrates how this flaw could enable attackers to establish more sophisticated attack chains, making prompt remediation essential for maintaining overall security posture.