CVE-2017-10872 in H2O
Summary
by MITRE
H2O version 2.2.3 and earlier allows remote attackers to cause a denial of service in the server via unspecified vectors.
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Analysis
by VulDB Data Team • 01/18/2023
The vulnerability identified as CVE-2017-10872 affects H2O version 2.2.3 and earlier, representing a significant security flaw that enables remote attackers to execute denial of service attacks against affected servers. This issue stems from unspecified vectors within the H2O web server implementation, creating potential pathways for malicious actors to disrupt service availability. The vulnerability specifically targets the server component of H2O, which is designed to provide high-performance web serving capabilities for machine learning and data science applications.
H2O is a popular open-source platform for machine learning that includes a built-in web server for serving models and providing user interfaces. The denial of service vulnerability in versions 2.2.3 and earlier indicates a fundamental weakness in how the server processes incoming requests or manages its resources, allowing attackers to exploit this weakness from remote locations without requiring authentication or privileged access. This type of vulnerability falls under the category of remote code execution and denial of service attacks, which are particularly dangerous as they can be exploited by anyone on the internet without prior access to the system. The unspecified nature of the attack vectors suggests that multiple pathways may exist for exploitation, making the vulnerability more difficult to fully understand and patch.
The operational impact of this vulnerability extends beyond simple service disruption, as it can potentially affect critical machine learning workflows and data science operations that depend on H2O's web server functionality. Organizations using affected versions of H2O may experience complete service outages, leading to downtime for model serving, user interface access, and administrative functions. The vulnerability's remote nature means that attackers can target systems from anywhere on the internet, making it particularly concerning for organizations that expose their H2O servers directly to public networks. This creates a substantial risk for enterprises relying on H2O for production machine learning services, as even a single successful exploitation could result in significant business disruption and potential data access issues.
Mitigation strategies for CVE-2017-10872 primarily involve upgrading to H2O versions that have addressed this vulnerability, with the specific patch details typically found in the vendor's security advisories. Organizations should also implement network-level protections such as firewalls and intrusion detection systems to monitor for suspicious traffic patterns that may indicate exploitation attempts. Additionally, the vulnerability aligns with several ATT&CK framework techniques including T1499 for network denial of service and T1071 for application layer protocol usage, which can help security teams identify and respond to exploitation attempts. Organizations should also consider implementing rate limiting and connection monitoring to detect anomalous behavior that might indicate exploitation attempts. The vulnerability demonstrates the importance of keeping web server software up to date and following secure configuration practices to minimize exposure to remote attack vectors. Given that this vulnerability affects a web server component, it also highlights the need for comprehensive security testing including penetration testing and vulnerability scanning to identify similar issues in other components of the H2O platform.