Description

Uncaught Exception (CWE-248) in Kibana can lead to a denial of service via Input Data Manipulation (CAPEC-153). An authenticated user holding only the low-privileged feature access required to use the Observability AI Assistant can submit a specially crafted request that produces an unhandled error condition, terminating the Kibana process and denying service to all users and spaces on that instance until it is restarted.

Executive Summary

Technical Details

Mitigations

References

Additional Metadata

{
  "score": "6.5",
  "pubDate": "2026-09-01T20:17:16.733Z",
  "pubdate": "2026-09-01T20:17:16.733Z",
  "executiveSummary": "A vulnerability categorized as CWE-248 (Uncaught Exception) exists within Kibana, specifically impacting the Observability AI Assistant feature. This flaw allows an authenticated user with low-privileged access to trigger an unhandled error condition through malicious input data manipulation (CAPEC-153). The successful exploitation of this vulnerability results in a complete denial-of-service (DoS) state, as the error causes the Kibana process to terminate unexpectedly. Because the failure forces the entire process to crash, the impact is system-wide, affecting all users and operational spaces on the affected instance. The service remains unavailable until manual intervention or an automated orchestration process performs a restart of the Kibana service. The vulnerability highlights a lack of proper input validation and exception handling within the Observability AI Assistant component, which poses a significant risk to availability in multi-tenant or shared Kibana environments where low-privileged users are granted access to these specific AI features.",
  "technicalDetails": "The vulnerability originates from inadequate error handling within the Kibana Observability AI Assistant component, specifically regarding the processing of user-supplied data. In environments where an Uncaught Exception (CWE-248) occurs, the application fails to encapsulate the error within a safe scope, allowing the exception to propagate to the top-level execution thread. This propagates the failure to the main process event loop, triggering an immediate and unrecoverable termination of the Kibana service.\nThe attack flow follows the CAPEC-153 pattern (Input Data Manipulation), where an authenticated user submits a specifically crafted request designed to exploit the parsing or processing logic of the AI Assistant. Because the application logic does not contain defensive programming patterns—such as try-catch blocks or robust input sanitization—to manage malformed or unexpected data payloads, the underlying Node.js runtime environment encounters an error it cannot recover from. When the process attempts to handle the malformed input, it generates an exception that remains unhandled, leading to a process crash.\nExploitation requires the attacker to possess legitimate, albeit low-privileged, access to the Observability AI Assistant feature. No special administrative rights or system-level privileges are required; the attacker simply needs the capability to interact with the API endpoints associated with the feature. The vulnerability is highly effective because it does not require significant computational overhead or advanced exploitation techniques; it leverages the existing, fragile state of the application's error handling. The post-exploitation impact is catastrophic for availability, as it effectively renders the Kibana instance unresponsive. All existing sessions are terminated, and any active tasks or dashboards become inaccessible to all users across all spaces. The persistence of the impact is absolute until the system is restarted, making it a critical concern for uptime-sensitive deployments. Network exposure is limited to the extent that the attacker must have network reachability to the Kibana service and valid authentication credentials, but the risk remains high given the ease of triggering the process crash."
}