CVE-2026-26940 in Kibana
Summary
by MITRE • 03/19/2026
Improper Validation of Specified Quantity in Input (CWE-1284) in the Timelion visualization plugin in Kibana can lead Denial of Service via Excessive Allocation (CAPEC-130). The vulnerability allows an authenticated user to send a specially crafted Timelion expression that overwrites internal series data properties with an excessively large quantity value.
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Analysis
by VulDB Data Team • 03/24/2026
The vulnerability identified as CVE-2026-26940 represents a critical weakness in the Timelion visualization plugin within the Kibana platform, specifically addressing improper validation of specified quantity in input as classified under CWE-1284. This flaw exists within the data processing pipeline of the visualization component where user-supplied Timelion expressions are parsed and executed without adequate validation of numerical parameters. The vulnerability manifests when an authenticated user crafts a malicious expression that manipulates internal series data properties by injecting excessively large quantity values. The root cause stems from insufficient input sanitization mechanisms that fail to validate the magnitude of numerical parameters before they are processed and stored within the system's memory structures.
The operational impact of this vulnerability extends beyond simple resource consumption to potentially compromise the entire Kibana instance through denial of service conditions. When an attacker exploits this weakness, the system experiences excessive memory allocation as internal series data properties are overwritten with artificially inflated values that can cause memory exhaustion and subsequent system instability. The CAPEC-130 classification indicates that this vulnerability specifically targets resource allocation mechanisms, making it particularly dangerous in environments where Kibana serves as a central monitoring and analytics platform. The excessive allocation occurs at the internal data structure level where series properties are manipulated, potentially leading to cascading failures that affect other components within the Elastic Stack ecosystem.
From a cybersecurity perspective, this vulnerability aligns with ATT&CK technique T1499.004 which focuses on network denial of service attacks through resource exhaustion. The authenticated nature of the exploit means that adversaries must first gain access to legitimate user credentials, but once achieved, they can leverage this weakness to disrupt services without requiring privileged access. The vulnerability demonstrates a classic example of how input validation flaws can be weaponized to cause system instability, particularly in visualization platforms where complex data processing operations are common. Organizations utilizing Kibana with Timelion plugins face significant risk exposure, as this vulnerability can be exploited to render the entire analytics platform unavailable to legitimate users.
Mitigation strategies should focus on implementing robust input validation mechanisms that enforce reasonable bounds on numerical parameters within Timelion expressions. System administrators should consider implementing rate limiting and resource quotas to prevent excessive memory allocation patterns from causing system-wide failures. The recommended approach includes deploying automated monitoring solutions that can detect anomalous allocation patterns and trigger alerts when suspicious resource consumption is observed. Additionally, organizations should implement network segmentation and access controls to limit the attack surface and reduce the likelihood of unauthorized access to Kibana instances. Regular security updates and patches should be prioritized, as this vulnerability represents a known weakness that can be exploited to cause significant operational disruption in monitoring environments.