Secure & Compliant AI Assistants

Security and compliance cannot be retrofitted after adoption; they shape core architecture choices (index partitioning, logging schemas, redaction pipelines) from day one. AI assistants introduce novel risks: amplified data extraction, model prompt injection, inadvertent PII leakage, cross‑tenant retrieval bleed. This pillar defines a pragmatic threat model and actionable controls mapped to common frameworks (SOC 2, GDPR) while preserving development velocity.

Threat Model Overview

Primary risk categories:

• Cross‑Tenant Data Leakage (improper filter reliance)
• Prompt Injection / Context Manipulation (malicious content altering behavior)
• Sensitive Data Exfiltration (PII, keys in logs or answers)
• Model Abuse (jailbreak attempts, generating disallowed content)
• Supply Chain (malicious dependency, compromised build pipeline)
• Observability Overreach (collecting more than necessary → privacy risk)

Treat model as untrusted code: bound inputs, sanitize context, validate outputs.

Tenant Isolation

Defense in depth:

1. Physical / Logical Partition: Separate collections or DB namespaces per tenant.
2. AuthZ in Retrieval Layer: Signed token containing tenant_id, role, plan; validated before any query execution.
3. Row‑Level Security Guard: Even if wrong collection touched, per‑record tenant_id assertion.
4. Service Account Scoping: Retrieval microservice only permitted read on specific tenant partitions.
5. Egress Policies: Disallow direct model internet calls; proxy with policy enforcement.

Never rely solely on metadata filters inside a shared vector index for hard isolation.

Data Minimization & Retention

Principles:

• Collect Only Necessary Fields (no full raw request bodies if truncated context suffices).
• PII Redaction Pipeline (regex + ML light classifier) before storage.
• Configurable Retention: e.g., 30 days default conversational logs; deletion job enforces SLA.
• Encryption: TLS in transit; at rest AES‑256 (cloud KMS managed keys); rotate keys annually or on incident.
• Right to Erasure: Deletion cascade (indices, logs, backups) tracked via job status audit.

Access Control & Auditing

RBAC Layers:

• Platform Admin (manage tenants, no raw PII viewing)
• Tenant Admin (configure scopes, view aggregated metrics)
• Analyst (read anonymized logs)
• Support Agent (view per‑session context within tenant)

Audit Log Fields: timestamp, actor_id, role, action, target_type, target_id, result, correlation_id. Store append‑only (WORM bucket / immutable log service). Monitor anomalous access patterns (sudden spike in export actions).

Compliance Domains

Mapping:

• GDPR: Data minimization (pipeline filters), purpose limitation (scoped usage), right to access (export tool), right to erasure (verified cascade deletes), data residency (regional index clusters).
• SOC 2: Change management (prompt/model version logs), logical access (RBAC + SSO), system monitoring (alerts on anomalous retrieval volume), incident response runbooks.
• CCPA: Consumer request workflow & disclosure transparency.

Document a Control Matrix linking each requirement to implemented mechanism.

Incident Response

Lifecycle:

1. Detection: Anomaly alerts (spike in refusal bypass, retrieval cross‑tenant miss, outbound data volume).
2. Triage: Classify severity, assemble response bridge.
3. Containment: Disable suspect prompt version, isolate compromised API keys, suspend affected tenant indexes if needed.
4. Eradication: Patch vulnerable code path (e.g., injection filter logic).
5. Recovery: Validate normal metrics baseline; re‑enable features progressively.
6. Postmortem: Root cause, timeline, control gaps, remediation tasks with owners.

SLO: Initial triage <30m for Sev1.

Secure Deployment

Practices:

• Secrets: Vault/KMS injection at runtime (no .env committed), short‑lived tokens.
• SBOM Generation: Track transitive deps; alert on critical CVEs.
• Build Integrity: Signed artifacts (cosign), branch protection & mandatory reviews.
• Runtime Hardening: Minimal base images, read‑only FS where possible, seccomp profiles.
• Dependency Update Cadence: Weekly automated PRs + security review.

Continuous Assurance

Cadence:

• Quarterly Threat Model Refresh (new components, attack paths)
• Biannual External Pen Test + validated remediation tracking
• Monthly Access Review (privileged accounts delta)
• Weekly Vulnerability Scan of images + dependency diff
• Control Effectiveness KPIs (e.g., % encrypted traffic, time to privilege revocation)

Key Takeaways

• Isolation must be layered—collection partition + auth + RLS.
• Minimize & redact early; you cannot leak what you never store.
• Immutable, structured audit logs are core evidence assets.
• Treat model input/output as untrusted—sanitize both directions.
• Continuous assurance prevents control rot after initial certification.