CVE-2021-37936 in Kibana
Summary
by MITRE • 11/19/2022
It was discovered that Kibana was not sanitizing document fields containing HTML snippets. Using this vulnerability, an attacker with the ability to write documents to an elasticsearch index could inject HTML. When the Discover app highlighted a search term containing the HTML, it would be rendered for the user.
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Analysis
by VulDB Data Team • 04/29/2025
The vulnerability identified as CVE-2021-37936 represents a critical cross-site scripting flaw in the Kibana data visualization platform that directly impacts the security posture of organizations relying on Elasticsearch and Kibana for log analysis and monitoring. This issue stems from insufficient input sanitization within Kibana's document handling mechanisms, specifically when processing HTML content within document fields. The vulnerability exists in the Discover application component where search results are displayed, creating a pathway for malicious actors to inject and execute arbitrary HTML code within the user interface. The flaw allows attackers to manipulate document fields containing HTML snippets, which are subsequently rendered when users search for specific terms and the application highlights matching content.
The technical exploitation of this vulnerability occurs through the manipulation of document fields within Elasticsearch indices that Kibana accesses. When an attacker crafts a document containing HTML code within its fields and writes it to an index, the HTML content becomes persistent within the system. During subsequent searches within the Discover application, when the system highlights search terms that match the HTML content, the malicious code executes in the context of the victim's browser session. This represents a classic cross-site scripting vulnerability that falls under CWE-79, which specifically addresses cross-site scripting flaws in web applications. The vulnerability is particularly dangerous because it leverages legitimate application functionality to deliver malicious payloads, making it difficult to detect through traditional security monitoring approaches.
The operational impact of CVE-2021-37936 extends beyond simple code execution, as it enables attackers to perform session hijacking, steal sensitive information, and potentially escalate privileges within the Kibana environment. The vulnerability allows for the execution of malicious scripts that can capture user credentials, redirect users to malicious sites, or perform actions on behalf of authenticated users. Attackers can craft payloads that exploit the highlighting feature to inject scripts that persist across multiple user sessions, creating a long-term threat vector within the organization's monitoring infrastructure. The attack surface is particularly concerning because Kibana is often used by security teams and administrators who may have elevated privileges, making successful exploitation potentially devastating for the overall security posture. This vulnerability also aligns with ATT&CK technique T1566, which covers social engineering through malicious content delivery, as the HTML injection occurs through legitimate document creation processes.
Organizations should implement immediate mitigations including upgrading to patched versions of Kibana where available, as well as implementing additional security controls such as Content Security Policy headers to limit script execution capabilities. Network segmentation and access controls should be enforced to restrict write access to Elasticsearch indices, particularly those accessible through Kibana. Regular monitoring of document creation activities within Elasticsearch indices can help detect anomalous behavior that might indicate exploitation attempts. The vulnerability also highlights the importance of input validation and sanitization practices throughout the application stack, emphasizing the need for comprehensive security testing including dynamic application security testing and manual penetration testing to identify similar issues in other components of the data processing pipeline.