The most relevant development for our beat isn’t a shiny new model. It’s that the federal AI governance baseline is real, specific, and—crucially—portable into classified environments. As PubSecAI’s brief on EO 14110’s implementation makes clear, three pillars are verified: OMB’s M-24-10, NIST’s AI Safety Institute (and its consortium), and CISA’s secure AI development guidance. Post-2025 changes are unverified. That uncertainty matters to policy shops. It shouldn’t paralyze operators at IL5/IL6.
What that means in practice: the floor is set. The IC has enough scaffolding to act. M-24-10 ties agency risk management to NIST AI RMF 1.0 and mandates CAIOs, governance boards, inventories, impact assessments, and minimum practices. NIST AISI is standing up the measurement science—evaluation methods, red-teaming patterns, and content authenticity workstreams. CISA’s guidance fills the engineering gaps: how to build and operate AI systems securely.
The implications for compartmented environments are straightforward, if not easy.
Inventories without sunlight. We won’t publish use cases, but we must maintain complete internal inventories across compartments and clouds (C2E, IL5/IL6), mapping models, training data, fine-tunes, retrieval corpora, eval artifacts, and approvals. If you can’t enumerate it, you can’t govern it.
Translating NIST into air-gapped reality. AISI’s test methods and red-team schemas won’t drop into a closed enclave intact. Rehost the patterns and build an in-cleared T&E bench: mission-domain adversarial testing, model-behavior drift detection on classified corpora, and fail-safe controls wired to real-world consequence thresholds.
Zero trust for model supply chains. Treat models and datasets like code with secrets: provenance, attestation, and isolation by default. Require model “SBOMs” (weights lineage, training/fine-tune data sources, eval results, safety constraints) and vendor attestations. Verify inside the boundary; don’t trust external paperwork.
Content authenticity is necessary, not sufficient. Watermarking and provenance help on the open side. Inside the fence, insist on signed inference pipelines, end-to-end content origin labels, and tamper-evident logs that survive cross-domain movement. Tie those signatures to your decision trails.
Procurement as a control surface. M-24-10 strengthens acquisition expectations. Use them. Bake in pretraining data lineage, fine-tune traceability, red-team reports, and model-update notification SLAs. Penalize opacity. Make managed services at IL5/IL6 meet the same bar as bring-your-own-model in platform enclaves.
Continuous authorization, not one-and-done ATO. Models drift; risks change with new corpora and adversary countermeasures. Move to continuous monitoring for AI systems—telemetry, behavioral baselines, and rollback paths—tied to your governance board, not just your ISSM.
The politics may shift; PubSecAI rightly flags post-2024 status as unverified. But the engineering truths won’t. Aligning to NIST AI RMF, adopting secure development practices, and institutionalizing model provenance and evaluation will not be wasted work under any administration.
What to do now
- Stand up an internal AI inventory across all classified enclaves; include models, datasets, RAG stores, evals, and authorities to operate.
- Establish a cleared AI T&E function. Start with mission-relevant red-team scenarios and drift monitoring on representative classified data.
- Require model/dataset SBOMs and provenance attestations in every contract and interagency agreement; verify inside the enclave.
- Implement zero-trust patterns for model serving: per-request authN/Z, data minimization, context isolation, and egress controls.
- Rehost AISI-aligned evaluation harnesses in IL5/IL6; track metrics that correlate to mission harm, not just academic benchmarks.
- Integrate content origin signing and tamper-evident logging into cross-domain solutions and analyst tooling.
- Update ATO playbooks for continuous authorization of AI systems; wire telemetry to governance boards chaired by your CAIO.
- Map CISA’s secure AI guidance to your SDLC and DevSecOps pipelines; audit quarterly.
What to watch
- NIST AISI’s next tranche of test and measurement artifacts and how feasible they are to reconstitute in air-gapped IL6.
- Any authoritative confirmation of EO 14110 status post-2024; treat it as operative until you see a signed superseding directive.
- Vendor readiness to provide model/data SBOMs and attestations at classification; who can prove lineage, and who can’t.
*Marcus Webb is a PubSecAI editorial persona — an AI-generated voice written to represent practitioner perspectives in the intelligence community sector. Views expressed are analytical commentary based entirely on open sources. No classified information is reflected or implied. *