A security and governance checklist for AI and LLM integration.
An open-source, interactive checklist that helps developers ship AI-powered features responsibly. Covers prompt security, data privacy, LLM monitoring, model governance, cost control, and regulatory compliance.
A single-page reference for teams integrating Large Language Models (LLMs) into production applications. Each item describes what to check, why it matters, and its severity — from critical to low.
40 items across 8 categories:
1 LLM Security 7 items
2 Privacy & Compliance 6 items
3 Application Security 4 items
4 Infrastructure & Operations 5 items
5 LLM Monitoring & Observability 5 items
6 Model Governance 5 items
7 Cost Management 4 items
8 UX & Responsible AI 4 items
→ Open the interactive checklist
Or clone it locally:
git clone https://github.com/mhmdgazzar/AI-Check.git
open AI-Check/checklist.htmlProgress is saved to your browser's local storage. No server, no tracking, no dependencies.
Integrating LLMs into real products introduces risks that traditional security checklists don't cover — prompt injection, hallucination mitigation, model drift, token cost management, EU AI Act compliance. This checklist consolidates these concerns into one actionable document.
Built from real-world experience shipping LLM-powered features in production.
| Category | Key Areas |
|---|---|
| LLM Security | Prompt injection, jailbreak resistance, hallucination grounding, bias audits, content moderation, red-teaming |
| Privacy & Compliance | GDPR, sensitive data handling, EU AI Act, copyright, audit logging, data retention |
| Application Security | XSS on AI outputs, CSRF/SSRF, session management, input validation |
| Infrastructure | API key management, rate limiting, fallback strategy, vendor lock-in, IAM |
| Monitoring | Latency tracking, token usage, response quality scoring, drift detection, error tracking |
| Model Governance | Versioning, rollback plans, evaluation benchmarks, model cards, A/B testing |
| Cost Management | Budget caps, per-request token limits, cost attribution, optimization review |
| Responsible AI | Human escalation, AI disclosure, user feedback, accessibility |
Open an issue or PR if you'd like to add items, improve descriptions, or translate the checklist. Keep items concise — title + one-line rationale.
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