Deploying an LLM runtime in a regulated environment (finance, healthcare, etc.) requires moving beyond generic "security features" to a verifiable control set. Based on several implementations, I've formalized a mandatory checklist. This is agnostic to the specific Claw variant, as the foundational principles apply across the board, though the implementation burden shifts.

**Core Pre-Deployment Verification**
* **Model Inventory & Provenance:** Document the exact model (vendor, version, hash). For fine-tuned models, the training data lineage and pipeline security controls must be traceable.
* **Runtime Isolation Model:** Map the runtime's isolation (process, container, VM, hardware) against your data classification. Confirm no unintended inter-agent communication channels exist. NanoClaw's container-per-agent versus IronClaw's hardware-enforced boundaries represent different points on this spectrum.
* **Credential Lifecycle:** How are API keys, database passwords, and service account tokens provisioned, injected, and rotated? The runtime must integrate with your existing vault (e.g., HashiCorp Vault, AWS Secrets Manager) without caching secrets in plaintext in memory logs.
* **Prompt Injection Surface Analysis:** Catalog all data inputs to the agent—user prompts, fetched web content, database records, API responses—and enforce structured validation or sanitation at each ingress point. Assume injection will be attempted.
* **Output Validation & Filtering:** Define a positive security model for outputs. This includes:
* Pre-commit hooks for code generation.
* PII redaction/scanners for all text outputs.
* Strict content allowlists for any autonomous actions (e.g., only these 5 API endpoints).

**Operational & Compliance Controls**
* **Immutable, Audit-Ready Logging:** All agent decisions, context window snapshots (pre/post-redaction), and taken actions must be logged to an immutable store. Logs must be sufficient to reconstruct the agent's "chain of thought" for an auditor.
* **Cost Attack Mitigation:** Implement hard, circuit-breaker limits on token consumption, tool usage, and external API calls per user/session. This is non-negotiable for public-facing agents.
* **Regulatory-Specific Mapping:** For HIPAA, ensure BAA is in place with the model vendor *and* runtime provider. For PCI, confirm no cardholder data enters the context window. For GDPR, document your lawful basis and ensure data subject deletion requests can propagate to any vector stores or agent memory caches.
* **Disaster Recovery & Integrity:** How is the agent state recovered? Are any "memories" or fine-tunes regularly backed up and integrity-checked? What is the failover procedure?

Choosing between NemoClaw, NanoClaw, and IronClaw becomes a matter of which runtime reduces the verification burden for your specific threat model. A heavily multi-tenant, public-facing use case leans toward IronClaw's hardware roots. An internal, single-tenant analytics agent might be adequately served by a rigorously configured NanoClaw instance with the above controls wrapped around it. The checklist, however, remains constant.

- Tracy