CVE-2026-107307 in SmartLinker AI
Summary
by MITRE • 10/30/2026
Incorrect Authorization vulnerability in Drupal SmartLinker AI allows Forceful Browsing. This issue affects SmartLinker AI versions: from 0.0.0 to 1.0.3.
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Analysis
by VulDB Data Team • 10/30/2026
The identified security flaw within the Drupal module known as SmartLinker AI, specifically affecting version ranges from 0.0.0 up through and including 1.0.3, represents a critical failure in access control mechanisms that facilitates forceful browsing attacks. This vulnerability stems from an incorrect authorization logic embedded within the application's backend processing routines. In secure software architecture, every request to a protected resource must be validated against the user's assigned permissions before any sensitive data is retrieved or processed. However, in this specific implementation, the module fails to adequately verify whether the authenticated user possesses the necessary privileges to access certain administrative functions or internal endpoints. Consequently, an attacker who has obtained valid credentials for even a low-privileged account can manipulate URL parameters or directly request URIs intended exclusively for administrators or higher-level roles. This bypass of authorization checks allows unauthorized entities to interact with parts of the system that should remain inaccessible, effectively elevating their privileges through simple navigation rather than exploiting complex code execution flaws.
From a technical perspective, this issue is classified under CWE-284, which denotes Improper Access Control, and more specifically aligns with CWE-639 regarding Authorization Bypass Through Forceful Browsing. The root cause lies in the absence of robust middleware or hook implementations that strictly enforce role-based access control (RBAC) policies on all exposed routes within the SmartLinker AI module. When a user attempts to access an endpoint, such as those responsible for configuring AI models, managing linked data sources, or viewing sensitive configuration files, the application does not cross-reference the request against the user's permission matrix. This oversight creates a predictable attack vector where malicious actors can enumerate internal paths and exploit them without needing additional authentication steps beyond their existing login session. The vulnerability is particularly dangerous because it relies on social engineering or simple reconnaissance rather than complex exploitation techniques, making it highly susceptible to automated scanning tools that routinely probe for common administrative paths like admin/settings or module-specific configuration pages.
The operational impact of this vulnerability extends far beyond mere unauthorized access; it poses a severe risk to the integrity and confidentiality of the entire Drupal environment hosting the SmartLinker AI module. An attacker leveraging forceful browsing can potentially modify critical system configurations, alter AI model parameters, or extract sensitive data stored within linked databases that are managed by the smart linking functionality. In many cases, administrative endpoints allow for the execution of scripts or changes to server-side settings, which could lead to further compromises such as remote code execution if combined with other misconfigurations. Furthermore, because SmartLinker AI likely handles external integrations and data pipelines, unauthorized access could result in the injection of malicious payloads into these workflows, compromising downstream systems that rely on the integrity of the linked information. This erosion of trust in the application's security posture can lead to significant business disruption, regulatory non-compliance due to data exposure, and potential financial losses associated with remediation efforts after a breach occurs.
To mitigate this vulnerability, immediate action is required by system administrators and developers maintaining instances of Drupal running SmartLinker AI versions 1.0.3 or earlier. The primary recommendation is to upgrade the module to the latest patched version where the authorization logic has been corrected to properly validate user permissions for all endpoints. If upgrading is not immediately feasible due to compatibility constraints, a temporary workaround involves implementing strict access controls at the web server level using tools like Apache's mod_authz_core or Nginx location blocks to deny direct access to known administrative paths unless accessed from trusted IP addresses. Additionally, organizations should review their existing user roles and permissions within Drupal to ensure that no unnecessary privileges are granted to low-level accounts, thereby reducing the attack surface available for forceful browsing attempts. Regular security audits and penetration testing focused on authorization bypasses can also help identify similar weaknesses in other modules before they are exploited by malicious actors.