Red Hat OpenShift AI
Red Hat OpenShift AI builds on the capabilities of Red Hat OpenShift to provide a single, consistent, enterprise-ready hybrid AI and MLOps platform. It provides tools across the full lifecycle of AI/ML experiments and models including training, serving, monitoring, and managing AI/ML models and AI-enabled applications.
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Red Hat OpenShift AI 3.5 EA2 Release notesEarly Access
Ensuring AI safety with guardrailsMaintain Safety
latest_security
| severity | advisory_cve | synopsis | date |
|---|---|---|---|
| severity Critical | advisory_cve(RHSA-2026:53263) RHOAI 3.3.6 - Red Hat OpenShift AI | synopsis RHOAI 3.3.6 - Red Hat OpenShift AI | date |
| severity Critical | advisory_cve(RHSA-2026:53262) RHOAI 3.4.3 - Red Hat OpenShift AI | synopsis RHOAI 3.4.3 - Red Hat OpenShift AI | date |
| severity Critical | advisory_cve(RHSA-2026:53261) RHOAI 2.25.10 - Red Hat OpenShift AI | synopsis RHOAI 2.25.10 - Red Hat OpenShift AI | date |
| severity Moderate | advisory_cveCVE-2026-70629 | synopsis A flaw was found in FFmpeg. An uninitialized heap memory read vulnerability exists in the native RSCC decoder. An attacker can supply a crafted video file with a compressed tile that decompresses fewer bytes than required. This leads to the unwritten portion of an intermediate buffer being copied into the decoded frame, potentially exposing data from prior heap allocations or previous decoded frames. | date |
| severity Important | advisory_cveCVE-2026-67322 | synopsis A flaw was found in GitPython. A remote attacker can exploit a vulnerability in the Repo.clone_from() method by providing a specially crafted Git repository URL. This URL can contain references to environment variables, which are then expanded and included in the URL. This allows the attacker to exfiltrate sensitive environment variables, such as access keys or tokens, to an attacker-controlled server during the cloning process, leading to information disclosure. | date |
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