Apache HugeGraph-Server is an open-source graph database designed for managing and analyzing large-scale graph data. It is widely used by organizations requiring high-performance graph data solutions. HugeGraph-Server supports environments running Java8 and Java11. The software is often implemented in complex data analysis and storage systems, providing scalable and efficient graph database management.
The vulnerability CVE-2024-27348 allows Remote Code Execution (RCE) within the Apache HugeGraph-Server. Specifically, it affects versions prior to 1.3.0, compromising the security of the system. This vulnerability enables attackers to execute arbitrary commands remotely through the gremlin component. Proper mitigations should be implemented to secure the affected systems.
The Remote Code Execution vulnerability in Apache HugeGraph-Server is found within the gremlin component. It allows an attacker to execute arbitrary commands by exploiting a specific endpoint with crafted input data. The vulnerable parameter involves manipulating Java objects via reflection. This could potentially enable unauthorized actions on the server by sending a specially crafted POST request to the gremlin endpoint.
Exploitation of this vulnerability can lead to complete compromise of the affected server. Attackers could execute arbitrary commands, resulting in unauthorized access to sensitive data, disruption of services, and further network infiltration. The severity of this vulnerability is critical as it allows remote execution of commands without any prior authentication.
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References:
- http://www.openwall.com/lists/oss-security/2024/04/22/3
- https://hugegraph.apache.org/docs/config/config-authentication/#configure-user-authentication
- https://lists.apache.org/thread/nx6g6htyhpgtzsocybm242781o8w5kq9
- https://github.com/Zeyad-Azima/CVE-2024-27348
- https://www.incibe.es/incibe-cert/alerta-temprana/vulnerabilidades/cve-2024-27348
- https://nvd.nist.gov/vuln/detail/CVE-2024-27348
- Upgrade Apache HugeGraph-Server to version 1.3.0 or later.
- Implement strict input validation and sanitization for data processed by the gremlin component.
- Employ robust authentication and authorization mechanisms to restrict access to critical endpoints.
- Regularly monitor and audit server activity for any signs of exploitation or unusual behavior.
- Apply network-level controls to limit access to the server from untrusted sources.
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