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Compliance15 min read

SOC 2 for AI Pipelines: Turning Controls into Code

Translate SOC 2 trust principles into executable controls for LLMs: access, change management, monitoring, incident response, and data integrity—baked into your redaction gateway, restoration service, and observability stack.

AK

Alex Kim

January 18, 2025

Goal: make SOC 2 compliance a property of your system, not a yearly scramble. By encoding controls in your AI gateway and restoration service, you’ll produce audit evidence continuously while keeping developers fast.

Map SOC 2 criteria to AI reality

SOC 2’s Trust Services Criteria (Security, Availability, Processing Integrity, Confidentiality, Privacy) apply neatly to LLM pipelines—if you frame them as control points.

Security

  • Access control: ABAC on gateway and restoration service; SSO with MFA; service identities for automations.
  • Network security: Egress denies except via gateway; vendor endpoints pinned; mTLS where supported.
  • Change management: Policy-as-code repo with PRs, reviews, and CI tests; versioned prompts and templates.

Availability

  • Circuit breakers and failovers across vendors/models.
  • SLIs/SLOs (latency, error rates) with alerting and on-call.

Processing integrity

  • Input validation (size/type), output schema checks, and post-process redaction.
  • Idempotency keys to prevent duplicate side effects on retries.

Confidentiality

  • Inline redaction of PII/PHI/PAN; secrets blocked.
  • Restoration with reason codes; encrypted mapping vault with short retention.

Privacy

  • Subject rights enablement (indexing by pseudonymous IDs, re-redaction/erasure flows).
  • Retention configured and enforced; legal holds integrated.

Controls as code: what it looks like

Represent critical controls as configuration that is reviewed, tested, and deployed like software:

  • Policy files (YAML/JSON) defining entity actions by environment and destination.
  • Validation tests that run seeded texts through the gateway and compare expected detection/restoration outcomes.
  • Guardrails in CI that block merges introducing banned logging or bypassed redaction.

Evidence generation by default

Every request produces safe, structured logs: request ID, model, policy version, detection counts by entity, restoration events (who/what/why), latency, vendor outcome. Store in an immutable log store with retention matching policy; export daily snapshots to your audit evidence bucket.

Change management without pain

Prompts and templates are code-reviewed assets. Require approvals for policy changes; maintain a changelog with links to PRs, test results, and rollout notes. Canary risky changes to a small tenant first; rollback via routing table if needed.

Vendor management inside the pipeline

Track vendor versions, regions, and settings in code. Expose a dashboard that shows which tenants use which models and whether data-use flags (e.g., “don’t train on my data”) are set. For audits, export a single report listing subprocessor exposure and retention settings per tenant.

Incident response that understands LLMs

Run drills for prompt leaks and secret exposure: contain (revoke links, rotate keys), assess (entities, subjects, window), remediate (delete/re-redact), and improve (policy patch, test added). Log everything with timeline markers so postmortems are frictionless.

Availability and DR

Provision secondary vendors/models; test failover monthly. Keep restoration keys backed up with split knowledge or HSM-based key escrow. For DR, verify that your immutable logs and policy repos restore cleanly in a different region.

What the auditor wants to see

  • Architecture diagrams with control points.
  • Policies and their code representations.
  • Sample logs showing detections/restorations (redacted).
  • Access reviews for restoration service.
  • Change history with approvals and test artifacts.
  • Incident records with root-cause and corrective actions.

Runbook for your first SOC 2 on AI

  1. Week 1–2: Map controls to components; add gaps to backlog.
  2. Week 3–4: Implement policy-as-code and logging schema; add CI guardrails.
  3. Week 5–6: Build evidence exporters and dashboards; write initial procedures.
  4. Week 7–8: Dry-run audit with internal reviewers; fix gaps; lock scope.

Bottom line

When controls become code, compliance becomes continuous. Your gateway, restoration service, and observability stack can generate the proof you need—while giving engineers a fast, paved road to ship safely.

Tags:SOC 2 AIcontrols as codeaudit evidenceLLM logschange managementtrust services criteriagovernance

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