A strong security framework for AI‑powered SaaS treats AI features as high‑privilege automation surfaces. Constrain inputs (permissioned retrieval, minimization), constrain outputs (typed, policy‑gated actions with simulation and rollback), and make everything observable (decision logs, SLOs, budgets). Layer these controls atop standard security programs (SOC 2/ISO 27001/27701) and map them to privacy, fairness, and model‑risk requirements.
Framework layers (from ground to governance)
- Identity, tenancy, and access
- SSO/OIDC + MFA; RBAC/ABAC and row‑level security; tenant isolation (compute, storage, caches, embeddings); per‑tenant KMS/HSM keys; JIT elevation with audit.
- Data minimization and residency
- Purpose‑bound data maps; redact PII/PHI/PCI before prompts/embedding; context budgets and whitelists; region pinning, VPC/private inference, BYO‑key.
- Retrieval (RAG) hardening
- Index only permissioned content; apply ACL filters pre‑embedding and at query time; provenance (URI, owner, timestamp, jurisdiction) and freshness SLAs; refusal on low/conflicting evidence; citations in UI/logs.
- Model gateway and routing
- Central gateway enforcing timeouts, retries, quotas, per‑tenant budgets; no‑train flags; region‑aware routing; small‑first model selection; variant caps; separate interactive vs batch lanes.
- Tool/action controls (never free‑text)
- Tool registry with JSON Schemas; payload validation; policy‑as‑code gates (eligibility, limits, approvals, change windows, egress rules); simulation/impact preview; idempotency and rollback tokens.
- Safety and abuse prevention
- Prompt‑injection/jailbreak detection; content sanitization and allowlists; outbound egress filters; output classifiers (toxicity/PII leakage); refusal behavior.
- Observability and evidence
- End‑to‑end traces retrieve → reason → simulate → apply; immutable decision logs linking input → evidence → policy gates → action → outcome; masked fields; audit exports.
- Evaluations and CI/CD gates
- Golden evals for grounding/citation coverage, JSON/action validity, refusal correctness, safety/fairness slices; connector contract tests and canary probes; block on regressions.
- Incident response and resilience
- Playbooks: model/prompt rollback, tool kill switches, cache/index purge, key rotation, vendor failover; champion–challenger models; error budgets and degrade to suggest‑only.
- Compliance and model risk
- SOC 2/ISO 27001 controls extended with ISO 27701 (privacy); GDPR/CCPA DSR automation across prompts/outputs/embeddings/logs; model cards, DPIAs/MRAs, fairness dashboards.
Control catalog (checklist)
- Identity and tenancy
- SSO/OIDC + MFA; RBAC/ABAC; row‑level security
- Tenant‑scoped encryption for data, caches, embeddings; BYO‑key
- JIT elevation; access reviews; toxic‑combo/SoD checks
- Data and retrieval
- Data maps/ROPA; purpose tags; redaction before prompts/embedding
- ACLs pre‑embedding and at query; provenance/freshness/jurisdiction tags
- Refusal defaults; citations displayed
- Model gateway and FinOps
- No‑train flags; regional/VPC endpoints; quotas/budgets
- Small‑first routing; variant caps; batch vs interactive lanes
- Budget alerts; cost per successful action tracked
- Tools and actions
- JSON Schemas; validation; simulation/preview; idempotency; rollback
- Policy‑as‑code (eligibility, limits, approvals, change windows, egress)
- Egress allowlists; domain pinning; MTLS to partners
- Safety and monitoring
- Injection/jailbreak detectors; content sanitization; output filters
- Anomaly alerts: token/variant spikes, cross‑tenant probes, egress anomalies
- SLOs: groundedness, JSON/action validity, refusal correctness, p95/p99, reversal rate
- Evidence and audits
- Immutable decision logs; signer identities; hash/timestamped artifacts
- Audit export bundles; model/prompt registry with diffs and eval scores
- DSRs and retention
- Search/erase/export for prompts, outputs, embeddings, logs
- TTLs; suppression lists to prevent re‑ingest; environment‑based debug retention
Threat model and mitigations (quick map)
- Prompt/indirect injection → instruction firewalls, curated/allowlisted sources, refusal without citations, output egress filters.
- Cross‑tenant RAG leak → tenant‑scoped vector stores, ACLs pre‑embedding and at query, boundary canary probes.
- Free‑text tool abuse → schema validation, policy gates, simulation/approvals, idempotency, audit, rate limits.
- Cost/DoS via tokens/variants → quotas, variant caps, router mix enforcement, caching, separate batch lanes.
- Vendor/model misuse → no‑train DPAs, VPC/private inference, per‑request flags, version pinning, periodic vendor tests.
- Connector drift → contract tests, schema/semantic drift detectors, self‑healing PRs, circuit breakers.
Metrics to manage like SLOs
- Quality/safety: groundedness/citation coverage, JSON/action validity, refusal correctness, reversal/rollback rate.
- Security/privacy: unpermitted access events, cross‑region violations, injection detections, egress blocks, DSR time‑to‑close.
- Reliability/cost: p95/p99, router mix, cache hit, variant count, GPU‑seconds per 1k decisions, cost per successful action.
Operating playbook (60–90 days)
- Weeks 1–2: Baseline and guardrails
- Data maps and residency; permissioned RAG with ACLs/provenance; model gateway with no‑train, quotas, region pinning; tool schemas and policy gates; enable decision logs; set SLOs/budgets.
- Weeks 3–4: CI gates and tests
- Golden evals (grounding/JSON/safety/fairness) in CI; connector contract tests and canary probes; injection/egress tests; budget alerts; dashboards live.
- Weeks 5–6: Hardening and privacy ops
- Tenant‑scoped encrypted embeddings/caches with TTLs; DSR automation; output filters; anomaly alerts for retrieval/tokens/variants/egress; kill switches.
- Weeks 7–8: Resilience and compliance
- Champion–challenger; vendor private endpoints; incident drills (prompt rollback, cache purge, key rotation); audit exports; prep SOC 2/ISO and DPIAs.
Mapping to established frameworks (starter guide)
- SOC 2/ISO 27001: cover identity, change management, logging, access reviews; extend with decision logs and tool policy gates.
- ISO 27701/GDPR: purpose limitation, DSRs, residency; embed refusal/citations for transparency; privacy impact assessments for new AI features.
- NIST AI RMF/Model risk: document model purpose, data sources, evals, monitoring, rollback; fairness metrics and human oversight points.
Common pitfalls (and fixes)
- Letting models execute free‑text actions
- Fix: enforce schemas, policy gates, simulation, approvals; instant rollback.
- Indexing before permissions
- Fix: apply ACLs pre‑embedding and at query; re‑embed with scopes; boundary probes.
- Logging raw prompts/outputs
- Fix: structured, redacted logs with short retention; break‑glass access.
- “Big model everywhere” and no budgets
- Fix: small‑first routing, caches, variant caps, quotas; separate batch lanes; track CPSA.
Bottom line: An AI SaaS security framework = permissioned inputs + policy‑gated, typed outputs + continuous evidence and SLOs. Build these controls once—RAG hardening, model gateway, tool schemas with policy‑as‑code, decision logs, CI safety gates—and the platform stays secure, auditable, and cost‑controlled as features and scale grow.