CVE-2025-6544 – Deserialization Vulnerability in H2O-3 By CyberDudeBivash
Overview
A critical deserialization vulnerability has been identified in h2oai/h2o-3 versions <= 3.46.0.8.
This flaw allows attackers to:
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Read arbitrary system files
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Execute arbitrary code on affected systems
The vulnerability stems from improper handling of JDBC connection parameters, which can be exploited by bypassing regex validation using double URL encoding.
All users of affected versions are at risk.
Technical Details
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Component Affected: H2O-3 machine learning platform (JDBC connection handling).
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Vulnerability Type: Insecure deserialization + input validation bypass.
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Attack Vector:
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Attacker supplies maliciously crafted JDBC connection parameters.
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By applying double URL encoding, malicious payloads bypass existing regex filters.
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Payloads are then deserialized unsafely, allowing attackers to trigger file read or remote code execution (RCE).
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Impact:
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Full system compromise under the context of the H2O process.
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Potential lateral movement across environments where H2O-3 is integrated.
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Impacted Versions
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All versions of H2O-3 <= 3.46.0.8
Mitigation & Recommendations
Until a patched version is released:
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Upgrade:
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Monitor H2O.ai security advisories and upgrade immediately once a fixed release is available.
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Workarounds:
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Restrict exposure of H2O-3 instances to trusted networks only.
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Enforce WAF rules or middleware sanitization to block malicious JDBC parameters.
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Disable unnecessary JDBC connectors if not in use.
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Detection:
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Hunt for suspicious double-encoded JDBC parameters in logs.
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Monitor for unexpected file access or Java deserialization artifacts.
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Response:
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If compromise is suspected, isolate the host immediately.
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Conduct full forensic investigation of H2O-3 instances and connected systems.
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CyberDudeBivash Expert Note
This vulnerability highlights a recurring issue in Java-based platforms: unsafe handling of deserialization. Attackers continue to exploit serialization frameworks, JDBC drivers, and input validation weaknesses.
At CyberDudeBivash, we recommend organizations adopt a “Zero Trust Deserialization” strategy:
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Avoid direct deserialization of untrusted input.
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Enforce strict parameter whitelisting.
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Integrate AI-driven anomaly detection for RCE attempts.
References
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Affected Project: H2O.ai H2O-3
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CVSS score (pending) – estimated 9.8 (Critical) due to RCE impact.
cyberdudebivash.com | cyberbivash.blogspot.com | cryptobivash.code.blog
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