CVE-2026-84911 in AI Plugin
Summary
by MITRE • 10/22/2026
Improper Neutralization of Input During Web Page Generation ("Cross-site Scripting") vulnerability in Drupal AI (Artificial Intelligence) allows Stored XSS. This issue affects AI (Artificial Intelligence) versions: from 0.0.0 to 1.3.13, from 1.4.0 to 1.4.8.
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Analysis
by VulDB Data Team • 10/22/2026
The vulnerability identified as Improper Neutralization of Input During Web Page Generation represents a critical security flaw within the Drupal AI module, specifically manifesting as a Stored Cross-Site Scripting issue. This type of vulnerability arises when an application accepts user-supplied input and subsequently includes that data in web pages sent to other users without performing adequate validation or encoding checks. In the context of the Drupal AI module, which facilitates artificial intelligence functionalities within the Drupal content management system, this flaw allows attackers to inject malicious scripts into areas where they are likely to be viewed by administrators or other legitimate users. The affected versions span from 0.0.0 up through 1.3.13 and from 1.4.0 through 1.4.8, indicating a persistent failure in input sanitization logic across multiple major releases of the module.
From a technical perspective, Stored XSS differs significantly from reflected variants because the malicious payload is permanently stored on the target server, typically within a database or content field associated with an AI-generated response or user profile. When another user accesses this compromised data, their browser executes the injected script in the context of the vulnerable site. This execution occurs under the trust relationship established between the user and the web application, allowing the attacker to bypass same-origin policy restrictions. The Drupal AI module likely fails to properly escape special characters such as angle brackets, quotes, or ampersands when rendering content that includes untrusted data derived from previous interactions with the AI interface. This lack of neutralization enables the injection of JavaScript code that can interact dynamically with the Document Object Model of the page being viewed by the victim.
The operational impact of this vulnerability is severe due to its stored nature, which ensures persistence and broad exposure without requiring complex social engineering tactics like phishing links for each attack instance. Once a malicious payload is successfully injected into an AI-related field or response, it will execute every time any user with access permissions views that specific content. This can lead to the theft of sensitive session cookies, authentication tokens, or personal data stored in local storage. Attackers can use this capability to hijack administrative sessions, potentially gaining full control over the Drupal installation. Furthermore, the injected scripts can perform actions on behalf of the victim, such as modifying site configurations, creating new user accounts with elevated privileges, or defacing the website interface. The presence of artificial intelligence features may also introduce unique attack vectors where AI-generated content is inadvertently used to mask malicious payloads, making detection by automated security tools more difficult.
This vulnerability aligns closely with CWE-79, which categorizes improper neutralization of input during web page generation as a classic cross-site scripting flaw. It also maps to the MITRE ATT&CK framework under techniques such as T1059, Command and Scripting Interpreter, specifically JavaScript execution within a browser environment. The persistence mechanism associated with stored XSS corresponds to tactics involving initial access or privilege escalation depending on the victim's role. To mitigate this risk, organizations running affected versions of the Drupal AI module must immediately upgrade to a patched version that addresses these input validation failures. Developers should implement strict output encoding using context-aware escaping techniques tailored for HTML body content and ensure that any data retrieved from storage is sanitized before being rendered in the browser interface. Additionally, deploying Content Security Policy headers can provide an additional layer of defense by restricting the sources from which scripts are allowed to execute, thereby limiting the impact even if a successful injection occurs. Regular security audits and code reviews focusing on input handling within AI-related modules are essential to prevent similar vulnerabilities in future updates.