CVE-2024-10572 — HIGH (CVSS 7.5) AI Security Vulnerability

Q: Is CVE-2024-10572 actively exploited?

No confirmed active exploitation of CVE-2024-10572 has been reported, but organizations should still patch proactively.

Q: How to fix CVE-2024-10572?

1. Immediately restrict network access to H2O's REST API port (default 54321) via firewall rules—allow only from trusted data science subnets or localhost. 2. Audit all H2O-3 deployments for internet or broad intranet exposure; treat any exposure as critical. 3. No official patch is available for versions <=3.46.0.1—monitor h2oai/h2o-3 GitHub releases and the GHSA-wjpv-64v2-2qpq advisory for fix availability. 4. Terminate H2O clusters when not actively in use to minimize exposure window. 5. Enable H2O audit logging and alert on XGBoostLibExtractTool invocations via the run_tool endpoint. 6. Consider placing H2O deployments behind an authenticated reverse proxy as an interim control until patching is possible.

Q: What systems are affected by CVE-2024-10572?

This vulnerability affects the following AI/ML architecture patterns: ML training pipelines, AutoML platforms, Distributed training clusters, Shared data science platforms, Jupyter/notebook environments with H2O backend, MLOps platforms.

Q: What is the CVSS score for CVE-2024-10572?

CVE-2024-10572 has a CVSS v3.1 base score of 7.5 (HIGH). The EPSS exploitation probability is 0.36%.

CISO Take

H2O-3 versions up to 3.46.0.1 expose a tool invocation API with no authentication, allowing anyone on the network to shut down your ML training server or exhaust disk storage. If your teams use H2O for AutoML or distributed training, immediately firewall port 54321 (H2O default) to restrict access to trusted networks only. No patch is currently available; network isolation is the primary mitigation until a fix ships.

Risk Assessment

CVSS 7.5 HIGH with no authentication, no user interaction, and a network-accessible attack vector makes this trivially exploitable by any attacker who can reach the H2O REST API port. EPSS of 0.00119 indicates limited current exploitation activity, but the zero-barrier entry lowers the risk of it remaining unexploited for long. H2O-3 is frequently deployed in data science environments with permissive network controls—shared Jupyter hubs, internal MLOps platforms, dev clusters—significantly elevating real-world exposure. The absence of a patch amplifies risk.

Affected Systems

Package	Ecosystem	Vulnerable Range	Patched
ai.h2o:h2o-ext-xgboost	maven	>= 3.34.0.1, <= 3.46.0.1	No patch
h2o	pip	>= 3.34.0.1, <= 3.46.0.1	No patch

Severity & Risk

CVSS 3.1

7.5 / 10

EPSS

0.4%

chance of exploitation in 30 days

Higher than 59% of all CVEs

Source: EPSS v3 — FIRST.org

Exploitation Status

Exploit Available

Exploitation: MEDIUM

Sophistication

Trivial

Exploitation Confidence

medium

○ CISA SSVC: Public PoC

Composite signal derived from CISA KEV, CISA SSVC, EPSS, trickest/cve, and Nuclei templates.

Attack Surface

AV Network

AC Low

PR None

UI None

S Unchanged

C None

I None

A High

Recommended Action

6 steps

Immediately restrict network access to H2O's REST API port (default 54321) via firewall rules—allow only from trusted data science subnets or localhost.
Audit all H2O-3 deployments for internet or broad intranet exposure; treat any exposure as critical.
No official patch is available for versions <=3.46.0.1—monitor h2oai/h2o-3 GitHub releases and the GHSA-wjpv-64v2-2qpq advisory for fix availability.
Terminate H2O clusters when not actively in use to minimize exposure window.
Enable H2O audit logging and alert on XGBoostLibExtractTool invocations via the run_tool endpoint.
Consider placing H2O deployments behind an authenticated reverse proxy as an interim control until patching is possible.

CISA SSVC Assessment

Decision Track*

Exploitation poc

Automatable Yes

Technical Impact partial

Source: CISA Vulnrichment (SSVC v2.0). Decision based on the CISA Coordinator decision tree.

Classification

DoS Code Execution Framework Training Data AML.T0029 - Denial of AI Service AML.T0049 - Exploit Public-Facing Application AML.T0050 - Command and Scripting Interpreter

Compliance Impact

This CVE is relevant to:

EU AI Act

Article 15 - Accuracy, Robustness and Cybersecurity

ISO 42001

A.9.4 - AI System Security Controls

NIST AI RMF

MANAGE 2.2 - Mechanisms to Sustain Deployed AI Systems

OWASP LLM Top 10

LLM03 - Supply Chain Vulnerabilities

Frequently Asked Questions

What is CVE-2024-10572?

H2O-3 versions up to 3.46.0.1 expose a tool invocation API with no authentication, allowing anyone on the network to shut down your ML training server or exhaust disk storage. If your teams use H2O for AutoML or distributed training, immediately firewall port 54321 (H2O default) to restrict access to trusted networks only. No patch is currently available; network isolation is the primary mitigation until a fix ships.

Is CVE-2024-10572 actively exploited?

No confirmed active exploitation of CVE-2024-10572 has been reported, but organizations should still patch proactively.

How to fix CVE-2024-10572?

1. Immediately restrict network access to H2O's REST API port (default 54321) via firewall rules—allow only from trusted data science subnets or localhost. 2. Audit all H2O-3 deployments for internet or broad intranet exposure; treat any exposure as critical. 3. No official patch is available for versions <=3.46.0.1—monitor h2oai/h2o-3 GitHub releases and the GHSA-wjpv-64v2-2qpq advisory for fix availability. 4. Terminate H2O clusters when not actively in use to minimize exposure window. 5. Enable H2O audit logging and alert on XGBoostLibExtractTool invocations via the run_tool endpoint. 6. Consider placing H2O deployments behind an authenticated reverse proxy as an interim control until patching is possible.

What systems are affected by CVE-2024-10572?

This vulnerability affects the following AI/ML architecture patterns: ML training pipelines, AutoML platforms, Distributed training clusters, Shared data science platforms, Jupyter/notebook environments with H2O backend, MLOps platforms.

What is the CVSS score for CVE-2024-10572?

CVE-2024-10572 has a CVSS v3.1 base score of 7.5 (HIGH). The EPSS exploitation probability is 0.36%.

Technical Details

NVD Description

In h2oai/h2o-3 version 3.46.0.1, the `run_tool` command exposes classes in the `water.tools` package through the `ast` parser. This includes the `XGBoostLibExtractTool` class, which can be exploited to shut down the server and write large files to arbitrary directories, leading to a denial of service.

Exploitation Scenario

An attacker with network access to an exposed H2O-3 REST API endpoint sends a crafted unauthenticated POST request invoking XGBoostLibExtractTool via the AST parser through the run_tool command interface. No credentials or prior access are required. In a denial-of-service scenario, the attacker triggers server shutdown, killing all active training jobs on a shared ML platform—potentially wiping hours or days of GPU compute time. In a disk exhaustion scenario, the attacker writes large files to arbitrary directories (e.g., shared NFS mounts or container volumes), causing cascading failures across the ML infrastructure. On a multi-tenant data science platform, a single unauthenticated request can disrupt the entire team's workloads simultaneously.