CVE-2026-111671 in Cube Studio
Summary
by MITRE • 10/16/2026
Cube-studio through 2026.09.01 contains an insecure direct object reference vulnerability that allows authenticated users to stop, reset, clear or redeploy other users' notebooks and services by id. Attackers can pass sequential ids to lifecycle endpoints in view_notebook.py, view_inferenceserving.py and view_serving.py to delete pods and take production inference endpoints offline.
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Analysis
by VulDB Data Team • 10/16/2026
Cube-studio versions up through 2026.09.01 are affected by a critical insecure direct object reference vulnerability that fundamentally compromises the integrity of multi-tenant resource management within machine learning operations environments. This flaw resides in the application logic governing notebook and inference service lifecycle endpoints, specifically within the view_notebook.py, view_inferenceserving.py, and view_serving.py modules. The core technical deficiency is a failure to enforce proper authorization checks when processing requests that target specific resources by their unique identifiers. Instead of validating whether the authenticated user initiating the request owns or has explicit permission to manage the targeted resource, the application blindly trusts the object identifier provided in the HTTP request parameters. This architectural oversight allows any authenticated user to manipulate arbitrary objects within the system simply by iterating through sequential integer values assigned to notebooks and services.
The operational impact of this vulnerability is severe, particularly in production environments where Cube-studio orchestrates critical machine learning workloads. An attacker with valid credentials can exploit this flaw to stop, reset, clear, or redeploy resources belonging to other users without authorization. By passing sequentially incremented identifiers to the affected lifecycle endpoints, an adversary can systematically delete pods associated with specific notebooks or inference services. This capability effectively allows for a denial of service against colleagues and disrupts ongoing computational tasks. More critically, because these actions extend to production inference endpoints, attackers can take live machine learning models offline, causing significant business disruption and potential data integrity issues if the redeployment process involves overwriting existing configurations with malicious defaults or empty states.
From a classification perspective, this vulnerability aligns directly with CWE-639, which describes authorization bypass through direct object references. The attack vector leverages predictable identifier schemes to enumerate valid resources and execute unauthorized state changes. In terms of tactical mapping within the MITRE ATT&CK framework, this behavior corresponds to T1078 Valid Accounts, as it requires initial authentication, followed by T1499 Endpoint Denial of Service if the goal is disruption, or potentially T1562 Impair Defenses if the redeployment action disables security monitoring agents running within those pods. The lack of ownership verification represents a fundamental gap in role-based access control implementation for individual resource instances rather than just general application roles.
To mitigate this vulnerability, immediate remediation should focus on implementing robust authorization checks at the point of request processing within the identified Python modules. Developers must ensure that every API call validating an object identifier also verifies that the currently authenticated user is the legitimate owner or has been granted explicit administrative privileges for that specific resource ID. This can be achieved by maintaining a secure mapping between users and their resources in the database, checking this relationship before executing any destructive actions such as pod deletion or service reset. Additionally, implementing non-sequential, unpredictable identifiers for internal objects would significantly raise the barrier for enumeration attacks, although strict authorization checks remain the primary defense against insecure direct object references. Regular security audits of API endpoints should be conducted to ensure that all state-changing operations adhere to the principle of least privilege and validate ownership consistently across all service modules.