A security flaw in Red Hat OpenShift AI has raised serious concerns for organizations running artificial intelligence workloads in hybrid cloud environments. The flaw, tracked as CVE-2025-10725, could allow attackers to escalate privileges and gain full control of the infrastructure under certain conditions.
This vulnerability highlights the increasing risks faced by enterprises adopting AI-driven platforms, especially those used for managing large-scale predictive and generative AI (GenAI) models. Since hybrid and multi-cloud setups are now common, such flaws can create large attack surfaces for cybercriminals.
Red Hat OpenShift AI is a machine learning (ML) and GenAI lifecycle management platform. It helps organizations with:
- Data acquisition and preparation
- Training and fine-tuning models
- Serving AI models into production
- Monitoring model performance
- Hardware acceleration for large-scale AI
Many enterprises use OpenShift AI to build and deploy AI workloads across public clouds, private data centers, and hybrid environments. This makes the platform an attractive target for attackers looking to compromise AI infrastructure.
The flaw, identified as CVE-2025-10725, carries an extremely high CVSS score of 9.9/10, placing it just short of “Critical.”
According to Red Hat’s advisory, the vulnerability requires an attacker to already have access to an authenticated account. This means the attacker must log in as a low-privileged user—such as a data scientist using a Jupyter notebook—before exploiting the flaw.
Once inside, the attacker could escalate their privileges and become a full cluster administrator, gaining control of the entire system.
Red Hat explained:
“This allows for the complete compromise of the cluster’s confidentiality, integrity, and availability. The attacker can steal sensitive data, disrupt all services, and take control of the underlying infrastructure, leading to a total breach of the platform and all applications hosted on it.”
The flaw impacts the following product versions:
- Red Hat OpenShift AI 2.19
- Red Hat OpenShift AI 2.21
- Red Hat OpenShift AI (RHOAI)
Organizations running these versions should apply security updates immediately or follow the recommended mitigations.
If exploited, CVE-2025-10725 could allow attackers to:
- Access and steal sensitive enterprise or customer data
- Disrupt AI training and inference services
- Shut down applications hosted on the platform
- Gain full control over the hybrid cloud infrastructure
- Compromise confidentiality, integrity, and availability (CIA) of critical workloads
Given the growing reliance on AI for business operations, such an attack could cause financial loss, data exposure, and reputational damage.
Red Hat has not classified this flaw as “Critical,” mainly because it requires authentication. Still, the company urges customers to act quickly. Recommended mitigations include:
Follow the principle of least privilege
- Do not assign broad permissions to system-level groups.
- Grant job creation rights only to specific users or teams who absolutely need them.
Review ClusterRoleBinding configurations
- Avoid associating the kueue-batch-user-role with the system:authenticated group.
Apply Red Hat security patches as soon as they are available.
Monitor for unusual activity from low-privileged accounts, especially data scientists and developers using Jupyter notebooks.
By tightening access controls and applying updates, organizations can reduce the risk of privilege escalation attacks.
This incident shows how AI platforms are becoming a new attack vector in enterprise cybersecurity. Attackers are no longer just targeting traditional IT systems—they are moving toward platforms that manage machine learning and generative AI models.
With AI powering critical business decisions, attackers can cause widespread damage by compromising training data, model outputs, or infrastructure availability. This makes securing AI pipelines and platforms like OpenShift AI a top priority.
The discovery of CVE-2025-10725 in Red Hat OpenShift AI is a strong reminder for enterprises: privileged access risks must be taken seriously in AI and hybrid cloud deployments. Even if attackers need authenticated access, insiders or compromised accounts can serve as an entry point.
Organizations should implement least-privilege access controls, patch management, and continuous monitoring to stay protected.
As AI adoption continues to grow, so does the cybersecurity risk surface. Ensuring that platforms like Red Hat OpenShift AI are secured is not just a best practice—it’s essential for safeguarding enterprise data and operations in today’s hybrid cloud world.
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