ai-saas-security-review

Audit AI SaaS products for OWASP web risks and AI-specific threats.

1|Updated May 11, 2026

Search Tags:#OWASP #rate limiting #security review #RLS #ai prompt injection #webhook validation

Ready to run

npx skills add https://github.com/tlennon-ie/product-building-agents --skill ai-saas-security-review

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ai-saas-security-review
Source: https://github.com/tlennon-ie/product-building-agents/tree/main/.claude/skills/ai-saas-security-review
Command: npx skills add https://github.com/tlennon-ie/product-building-agents --skill ai-saas-security-review

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you reliably assess whether an AI SaaS is protected against common web security failures and AI-specific abuse (like prompt injection, jailbreaks, and system-prompt extraction), before vulnerabilities become incidents.

Core Features & Use Cases

Threat-layer security review: Organizes findings across identity, authorization, input, AI, action, and observability layers so severity judgments stay consistent.
OWASP + AI-specific checks: Covers classical web risks (authz, injection, XSS, CSRF, uploads, redirects, headers) plus AI risks (direct/indirect injection via memory or uploads, tool-output injection, jailbreak patterns).
Production hardening procedures: Provides concrete audit playbooks for RLS, webhook verification, secret scanning, rate limiting, admin surface protection, and a structured finding format.

Quick Start

Use this skill to review a pull request by mapping each code change to the six threat layers and producing CRITICAL/HIGH findings with repro steps and actionable fixes.

Frequently Asked Questions about ai-saas-security-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I conduct a security review for an AI SaaS application?▼

Conduct an AI SaaS security review by mapping code changes across six threat layers—identity, authorization, input, AI, action, and observability—to produce structured findings with severity definitions and actionable fixes.

What security checks are needed to prevent AI prompt injection and jailbreaks?▼

Security checks for AI prompt injection must validate direct and indirect injection vectors via memory or file uploads, scan tool-output injection paths, and detect jailbreak patterns using a structured threat model.

How do I audit multi-tenant authorization and RLS in a SaaS database?▼

Audit multi-tenant authorization and Row Level Security (RLS) by applying production hardening checklists to verify data isolation, validate webhook signatures, and ensure strict tenant boundary enforcement across endpoints.

Can I use an OWASP checklist to secure LLM flows and file uploads?▼

Yes, you can use an OWASP-style checklist to secure LLM flows by evaluating classical web risks like XSS, CSRF, and file upload vulnerabilities alongside AI-specific threats such as system-prompt extraction and tool-output injection.

What is the best way to structure security findings for merge-blocking decisions?▼

Structure security findings for merge-blocking decisions by categorizing threats into distinct layers and assigning CRITICAL or HIGH severity ratings with concrete reproduction steps and mitigation guidance.

How do I protect admin surfaces and validate webhooks in an AI application?▼

Protect admin surfaces and validate webhooks by executing production hardening procedures that enforce rate limiting, implement strict webhook signature verification, and apply secret scanning checklists across the application.