CVE-2026-110888 in AI Engine Plugin
Summary
by MITRE • 10/15/2026
Missing Authorization vulnerability in Meow Apps AI Engine ai-engine allows Exploiting Incorrectly Configured Access Control Security Levels.This issue affects AI Engine: from n/a through 3.8.3.
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Analysis
by VulDB Data Team • 10/15/2026
The identified vulnerability represents a critical failure in access control mechanisms within the Meow Apps AI Engine, specifically affecting versions ranging from non-existent initial releases up to version 3.8.3. This flaw is categorized under CWE-269, which denotes Improper Privilege Management, and more precisely aligns with CWE-862, Missing Authorization. The core technical issue lies in the application's inability to properly verify whether an authenticated user possesses the necessary permissions to perform specific actions or access certain resources within the AI Engine environment. Unlike authentication failures where a user is denied entry due to invalid credentials, this vulnerability allows any authenticated actor to bypass intended security restrictions simply by manipulating request parameters or exploiting logical gaps in the server-side authorization checks. This type of misconfiguration effectively renders existing role-based or attribute-based access controls ineffective for the affected components.
From an operational perspective, the impact of this missing authorization flaw is severe because it undermines the fundamental principle of least privilege that governs secure software architecture. An attacker who has obtained valid credentials through phishing, credential stuffing, or other means can leverage this vulnerability to escalate their privileges beyond what was originally assigned by the system administrator. This could lead to unauthorized access to sensitive data processed by the AI engine, manipulation of model configurations, or execution of administrative functions that should be restricted to high-level users. In the context of an AI application, such breaches may result in the extraction of proprietary training datasets, injection of malicious prompts to alter model behavior, or complete compromise of the underlying infrastructure if those privileged actions extend beyond the immediate application layer into system administration tasks.
The vulnerability is further contextualized by its alignment with MITRE ATT&CK technique T1078, Valid Accounts, as it relies on legitimate credentials being used for unauthorized purposes due to flawed server-side logic rather than credential theft alone. It also reflects aspects of T1548, Abuse Elevation Control Mechanism, if the lack of authorization allows a lower-privileged user to perform actions typically reserved for higher-privileged roles. The absence of robust checks means that the application trusts client-supplied data regarding identity and intent without sufficient validation against server-side policy definitions. This is particularly dangerous in AI engines where complex workflows often involve multiple steps with varying security requirements, making it difficult for automated monitoring tools to distinguish between legitimate high-level operations and malicious exploitation attempts based solely on request patterns.
To mitigate this vulnerability, immediate action must be taken by upgrading the Meow Apps AI Engine to a version later than 3.8.3 where these access control checks have been corrected. For organizations unable to upgrade immediately due to compatibility or deployment constraints, compensating controls should be implemented at the network perimeter using Web Application Firewalls configured with rules that detect anomalous privilege escalation attempts or unauthorized API calls. Additionally, developers must conduct a thorough code review focusing on all endpoints exposed by the AI engine to ensure that every action is preceded by an explicit authorization check against the user's assigned roles and permissions. Implementing strict input validation and enforcing server-side session management can further reduce the attack surface. Regular security audits and penetration testing focused specifically on broken access control scenarios are recommended to identify similar logical flaws in other parts of the application ecosystem before they can be exploited in production environments.