A vulnerability in the h2oai/h2o-3 repository allows attackers to exploit deserialization of untrusted data, potentially leading to arbitrary code exe...
Description
A vulnerability in the h2oai/h2o-3 repository allows attackers to exploit deserialization of untrusted data, potentially leading to arbitrary code execution and reading of system files. This issue aff...
AI Analyst Comment
Remediation
Update A vulnerability in the Multiple Products to the latest version. Monitor for exploitation attempts and review access logs.
Executive Summary:
A critical vulnerability has been identified in the H2O.ai H2O-3 platform, a widely used open-source machine learning tool. This flaw allows a remote, unauthenticated attacker to execute arbitrary code on the server by sending specially crafted data. Successful exploitation could lead to a complete system compromise, enabling attackers to steal sensitive data, disrupt services, or use the compromised system for further attacks.
Vulnerability Details
CVE-ID: CVE-2025-6507
Affected Software: H2O.ai H2O-3
Affected Versions: See vendor advisory for specific affected versions
Vulnerability: This vulnerability is classified as Deserialization of Untrusted Data. The H2O-3 application fails to properly validate and sanitize user-supplied data before it is deserialized. An attacker can construct a malicious object and serialize it into a data stream. When the vulnerable H2O-3 server processes this stream, it deserializes the object, which can trigger a chain of events that leads to the execution of arbitrary commands on the underlying operating system with the privileges of the H2O-3 service account.
Business Impact
This vulnerability is rated as critical severity with a CVSS score of 9.8, posing a severe and immediate risk to the organization. Exploitation can lead to a complete compromise of the affected server, resulting in significant business consequences. These include the potential for a major data breach involving sensitive corporate data or machine learning models, disruption of critical business operations that rely on the H2O-3 platform, and reputational damage. An attacker could also leverage the compromised server as a pivot point to launch further attacks against the internal network.
Remediation Plan
Immediate Action: The primary remediation is to update all instances of H2O.ai H2O-3 to the latest patched version provided by the vendor. After applying the update, it is essential to monitor for any signs of exploitation and review system and application access logs for any suspicious activity that may have occurred prior to patching.
Proactive Monitoring: Implement enhanced monitoring on systems running H2O-3. Security teams should look for unusual process execution spawned by the H2O-3 service (e.g.,
sh,cmd.exe,powershell.exe), unexpected outbound network connections, and anomalous file system modifications. Application logs should be reviewed for deserialization errors or malformed input warnings.Compensating Controls: If patching cannot be performed immediately, implement the following controls to reduce risk:
Exploitation Status
Public Exploit Available: False
Analyst Notes: As of the publication date, September 1, 2025, there are no known public exploits or active exploitation campaigns targeting this vulnerability. However, due to the critical severity (CVSS 9.8) and the direct path to Remote Code Execution, it is highly likely that threat actors will prioritize developing a functional exploit. Organizations should operate under the assumption that exploitation is imminent.
Analyst Recommendation
Given the critical CVSS score of 9.8, this vulnerability presents a significant and direct threat to the confidentiality, integrity, and availability of affected systems. The highest priority is the immediate patching of all vulnerable H2O-3 instances. Although this CVE is not currently on the CISA KEV list, its severity makes it a prime candidate for future inclusion. We strongly recommend that organizations apply the vendor-supplied updates without delay. If immediate patching is not feasible, the compensating controls outlined above must be implemented to mitigate the risk of a system compromise.