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. … Read more
Data leaks in AI SaaS happen when sensitive content slips into prompts, retrieval indexes, embeddings, logs, tool‑calls, or vendor pipes. Prevent them by constraining what models can see (permissioned retrieval and minimization), what they can do (typed, policy‑gated actions), and where data can go (egress controls and private inference). Make privacy observable with immutable decision … Read more
AI‑powered SaaS expands the attack surface: prompts, retrieval indexes, embeddings, model gateways, tool‑calls, and decision logs introduce new paths for data exfiltration, account takeover, and policy bypass. Treat AI features like high‑privilege automation endpoints: enforce identity and least privilege, harden retrieval and prompts against injection, constrain actions to typed schemas with policy‑as‑code, and monitor for … Read more