CVE-2022-31073 is a vulnerability classified under CWE-400 (Uncontrolled Resource Consumption) affecting the open-source project KubeEdge, which extends container orchestration capabilities to edge computing nodes. Specifically, the flaw resides in the ServiceBus server component on the edge side. In affected versions prior to 1.9.4, between 1.10.0 and 1.10.2 (exclusive), and version 1.11.0, the ServiceBus server does not properly limit the size of HTTP request bodies it processes. An attacker can exploit this by sending an HTTP request with an excessively large body to the ServiceBus server, causing the node to exhaust its available memory resources. This memory exhaustion leads to denial of service (DoS) conditions not only for the ServiceBus module but also for other services and containers running on the same node, as they fail to allocate memory. The vulnerability requires that the ServiceBus module be enabled in the edgecore.yaml configuration file, and that the attacker has the ability to send HTTP requests to localhost on the edge node. This implies that malicious applications running on the host or containers with localhost access can trigger the attack. The vulnerability has been addressed in KubeEdge versions 1.11.1, 1.10.2, and 1.9.4 by implementing proper request size validation or resource limits. As a temporary mitigation, disabling the ServiceBus module in the configuration file prevents exploitation. There are no known exploits in the wild reported to date. The vulnerability impacts the availability of edge nodes by enabling resource exhaustion through unregulated HTTP request sizes, potentially disrupting edge computing workloads and services dependent on KubeEdge's orchestration capabilities.

For European organizations leveraging edge computing infrastructures, particularly those using KubeEdge for container orchestration at the edge, this vulnerability poses a significant risk to service availability. Edge nodes often operate in resource-constrained environments and support critical applications such as IoT data processing, industrial automation, and real-time analytics. A successful exploitation could lead to denial of service on edge nodes, disrupting these critical services and potentially causing cascading failures in distributed systems. This disruption could affect sectors like manufacturing, smart cities, telecommunications, and energy management, where edge computing is increasingly deployed. Furthermore, since the attack can be launched from within the host or containers with localhost access, compromised or malicious workloads could be leveraged to trigger the DoS, increasing the risk from insider threats or supply chain compromises. The impact on confidentiality and integrity is minimal, as the vulnerability primarily affects availability. However, service outages at the edge could indirectly affect data collection and processing pipelines, leading to operational inefficiencies and potential compliance issues with data availability requirements.

1. Upgrade KubeEdge to versions 1.11.1, 1.10.2, or 1.9.4 or later where the vulnerability is patched. This is the most effective and recommended mitigation. 2. If immediate upgrade is not feasible, disable the ServiceBus module in the edgecore.yaml configuration file to prevent the vulnerable component from running. 3. Implement strict network segmentation and access controls to limit which containers or applications can send HTTP requests to localhost on edge nodes, reducing the risk of malicious internal actors exploiting the vulnerability. 4. Monitor edge node resource usage closely for abnormal memory consumption patterns that could indicate attempted exploitation. 5. Employ runtime security tools to detect and block anomalous HTTP requests with unusually large bodies targeting the ServiceBus server. 6. Conduct regular security audits of container images and workloads deployed on edge nodes to prevent introduction of malicious applications capable of exploiting this vulnerability. 7. Establish incident response procedures specifically for edge node service disruptions to minimize downtime and impact.