CVE-2019-11254 in Kubernetes
Summary
by MITRE
The Kubernetes API Server component in versions 1.1-1.14, and versions prior to 1.15.10, 1.16.7 and 1.17.3 allows an authorized user who sends malicious YAML payloads to cause the kube-apiserver to consume excessive CPU cycles while parsing YAML.
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Analysis
by VulDB Data Team • 01/08/2025
The vulnerability identified as CVE-2019-11254 affects the Kubernetes API Server component and represents a significant performance degradation issue that can be exploited through YAML payload manipulation. This vulnerability exists in Kubernetes versions ranging from 1.1 through 1.14, as well as in earlier releases before the patched versions 1.15.10, 1.16.7, and 1.17.3. The flaw specifically targets the YAML parsing mechanism within the kube-apiserver process, which serves as the central control plane component responsible for handling all API requests and maintaining cluster state.
The technical nature of this vulnerability stems from inefficient YAML parsing algorithms that exhibit exponential time complexity when processing malformed or specially crafted YAML payloads. When an authorized user submits malicious YAML content to the API server, the parsing logic enters into a computationally expensive loop that consumes disproportionate CPU resources relative to the payload size. This behavior creates a denial of service condition where legitimate API requests may experience significant delays or complete failure to process due to the server being overwhelmed by CPU-intensive parsing operations. The vulnerability operates at the application layer and leverages the legitimate API server functionality to create an abuse vector that can be triggered through normal user authentication and authorization processes.
From an operational impact perspective, this vulnerability presents a serious risk to Kubernetes cluster availability and performance. The excessive CPU consumption can lead to cascading failures within the cluster as the API server becomes unresponsive to legitimate requests, potentially affecting critical workloads and cluster management operations. Attackers can exploit this weakness to perform resource exhaustion attacks that degrade cluster performance without requiring elevated privileges beyond standard user access. The vulnerability also has implications for cluster scalability and reliability, as the API server's performance degradation can affect the entire cluster's ability to process requests efficiently and maintain service availability.
The security implications extend beyond simple performance degradation to include potential service disruption and resource exhaustion attacks that could be used in conjunction with other exploitation techniques. Organizations utilizing affected Kubernetes versions face increased risk of operational disruptions and may experience difficulties in maintaining cluster stability during peak usage periods. The vulnerability demonstrates the importance of proper input validation and parsing efficiency in critical system components, as inefficient parsing algorithms can create significant security implications even when the input is properly authorized. This issue aligns with CWE-400 which addresses excessive resource consumption and represents a classic example of a resource exhaustion vulnerability that can be exploited through carefully crafted inputs.
Mitigation strategies for CVE-2019-11254 primarily focus on upgrading to patched versions of Kubernetes where the YAML parsing logic has been optimized to prevent exponential time complexity. Organizations should prioritize immediate deployment of the security patches for versions 1.15.10, 1.16.7, and 1.17.3, depending on their current Kubernetes version. Additionally, implementing proper rate limiting and resource quotas at the API server level can help mitigate the impact of such attacks by limiting the computational resources available to individual requests. Network-level monitoring should be enhanced to detect unusual CPU consumption patterns that may indicate exploitation attempts. The remediation approach should also include implementing proper YAML validation and sanitization processes to prevent malicious payloads from reaching the core parsing logic. Organizations should consider implementing API request throttling mechanisms and monitoring for anomalous parsing behavior as part of their overall security posture. This vulnerability serves as a reminder of the importance of algorithmic efficiency in security-critical components and the need for comprehensive testing of parsing logic against malicious inputs.