CVE-2026-72667 in Kibana
Summary
by MITRE • 08/13/2026
Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to a denial of service via Excessive Allocation (CAPEC-130). A specially crafted request submitted by an authenticated user with minimal privileges to a validation capability of the Observability log analysis feature causes Kibana to perform an unbounded amount of concurrent work. This can exhaust the memory available to the Kibana process and make Kibana unavailable to all users until it is restarted. The severity of the outcome depends on the resources allocated to the deployment; on well-provisioned deployments a single request may cause degraded performance and elevated memory pressure rather than a full outage, but the request is inexpensive to repeat.
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Analysis
by VulDB Data Team • 08/13/2026
The vulnerability described represents a critical resource allocation flaw that fundamentally undermines system availability and operational stability within Kibana's observability framework. This issue manifests as an improper handling of resource consumption during log analysis validation processes, where authenticated users can exploit a weakness in input processing to trigger unlimited concurrent operations. The vulnerability operates through the Observability log analysis feature's validation capability, which lacks proper bounds checking or throttling mechanisms to control resource utilization. When a maliciously crafted request is submitted, it initiates an unbounded amount of concurrent work that rapidly consumes available memory resources without any mechanism to limit or control the scope of execution.
The technical implementation of this vulnerability stems from inadequate resource management within Kibana's internal processing pipelines, where validation operations fail to enforce limits on concurrent threads, memory allocation, or computational resources. This flaw directly maps to CWE-770, which specifically addresses the allocation of resources without proper constraints or monitoring, creating a pathway for attackers to exhaust system resources through seemingly benign operations. The attack vector requires only minimal privileges and can be executed through standard user authentication mechanisms, making it particularly dangerous as it can be exploited by users who should normally have restricted access levels. The design flaw allows the system to scale infinitely in resource consumption rather than maintaining bounded processing limits that would prevent such exhaustion scenarios.
The operational impact of this vulnerability extends beyond simple service disruption to encompass significant business continuity risks and performance degradation across the entire Kibana deployment. Memory exhaustion caused by the excessive allocation can lead to complete system unavailability, forcing administrators to perform manual restarts and potentially causing data loss or incomplete analysis operations. Even in well-provisioned environments where immediate full outages are prevented, the vulnerability creates persistent memory pressure that degrades overall system performance and can affect other applications sharing the same infrastructure. The economic implications are substantial as organizations face increased operational overhead from frequent restarts, potential service level agreement violations, and the need for emergency maintenance procedures.
Mitigation strategies must address both immediate defensive measures and long-term architectural improvements to prevent similar vulnerabilities from occurring in production environments. Organizations should implement resource throttling mechanisms that limit concurrent operations and memory allocation within Kibana's validation processes, while also establishing monitoring systems that can detect unusual resource consumption patterns and automatically trigger alerts or protective measures. The implementation of proper input validation and rate limiting controls becomes critical in preventing exploitation, particularly for features that process user-submitted data such as log analysis capabilities. Security teams should also consider implementing network-level controls to restrict access to potentially vulnerable endpoints and establish baseline resource utilization metrics to quickly identify when systems are approaching dangerous consumption thresholds. This vulnerability exemplifies the importance of applying principle of least privilege and defense in depth strategies, ensuring that even authenticated users cannot inadvertently or maliciously cause system-wide resource exhaustion through well-designed boundary controls. The remediation process should also include comprehensive testing of resource management controls to validate that proper limits are enforced and that system behavior remains predictable under various load conditions.