Apache Hadoop YARN ResourceManager Injection Scanner

Apache Hadoop YARN ResourceManager is used widely in big data applications for managing resources in a cluster. Organizations and businesses leverage this framework to process large datasets across distributed computing environments. It's crucial for managing workloads in Hadoop clusters, ensuring resource allocation, job scheduling, and monitoring. YARN acts as a resource manager to balance loads within a distributed data processing system. Administrators administrate and configure these systems to optimize resource distribution and job execution. The software is critical in various sectors, including finance, healthcare, and tech, due to its robust data processing and analytics capabilities.

Remote Code Execution (RCE) is a critical vulnerability that allows attackers to execute arbitrary code on remote systems. This vulnerability could lead to unauthorized actions in the victim’s environment, enabling data theft or manipulation. It poses a significant risk as it can undermine system integrity and confidentiality. Attackers can exploit this to install malware, create backdoors, or further infiltrate a network. Detection of such vulnerabilities is vital in preventing unauthorized access to sensitive applications. Understanding RCE risks helps in strengthening the security posture and mitigating potential exploitation.

The technical aspect of this vulnerability involves the exploitation of weak points in REST API endpoints, particularly the "/ws/v1/cluster/apps/new-application" path. The vulnerability stems from improper handling of incoming data and lack of stringent authentication protocols. Attackers manipulate HTTP POST requests and monitor for specific application IDs to execute code remotely. Detection relies on identifying response patterns that indicate a successful unauthorized request. Attention to API endpoint security is critical in defending against RCE attempts. Ensuring accurate request validation and authentication can mitigate this vulnerability.

When exploited, RCE in Hadoop YARN can lead to severe consequences like unauthorized data access, system control, and destruction of data integrity. Malicious actors might install compromise tools or run malicious code to achieve their objectives. It could potentially disrupt services, causing financial and reputational damage. Organizations may face extensive recovery processes if unauthorized activities remain unnoticed. The vulnerability can expose critical information, leading to further attacks. Damage control and prevention strategies are essential to mitigate impacts if an RCE vulnerability is exploited.

REFERENCES

• http://archive.hack.lu/2016/Wavestone%20-%20Hack.lu%202016%20-%20Hadoop%20safari%20-%20Hunting%20for%20vulnerabilities%20-%20v1.0.pdf
• https://github.com/rapid7/metasploit-framework/blob/master/modules/exploits/linux/http/hadoop_unauth_exec.rb
• https://github.com/vulhub/vulhub/tree/master/hadoop/unauthorized-yarn
• https://github.com/Al1ex/Hadoop-Yarn-ResourceManager-RCE