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Guides securing AI workloads with SELinux: apply least-privilege policies; label models, datasets, logs, and GPU device files correctly; tune container contexts; audit and resolve AVC denials; use booleans, sandboxing, and MCS/MLS where appropriate; integrate policy modules into CI/CD; monitor drift; and favor performance tuning under enforcement over disabling SELinux.