Decision Guide · 1 minute read
AI Security Checklist for Enterprise Projects
An enterprise AI security checklist covers data handling (where data lives, who can access it, what's never sent to third parties), access control and least privilege, model and prompt security (injection defenses, output validation), monitoring and audit logging, and the vendor's security posture. Clear each item before AI touches production data.
Before AI touches production data, it must clear a security bar—and AI adds concerns traditional software doesn't have. Use this checklist to deploy safely.
Data handling
- Where does data live during processing and at rest?
- Who can access it—people, models, and integrations?
- What is never sent to third-party APIs?
- Residency and compliance requirements met?
See data security in AI development and private LLM vs public API.
Access control
- Least privilege for every model, agent, and service.
- Scoped credentials, rotated and monitored.
- Segregation between environments.
Model and prompt security
- Prompt injection defenses (the signature agent risk).
- Input validation on untrusted data.
- Output validation before actions take effect.
- Human approval for high-stakes actions.
Monitoring and audit
- Logging of every AI action (observability).
- Audit trail for compliance.
- Incident response plan and escalation.
Vendor security questions
| Ask | Why |
|---|---|
| Where is data processed and stored? | Residency and exposure |
| How is access controlled and logged? | Least privilege + audit |
| How do you defend against injection? | Agent-specific risk |
| What's your compliance posture? | Industry fit |
Vague answers are a red flag—see how to evaluate AI vendors.
Why FISTA
FISTA Solutions aligns security in discovery and builds it into delivery—least privilege, validation, monitoring, and audit—backed by a verified 99.9% uptime record across 150+ projects. Explore AI enablement.
Securing an AI deployment? Talk to FISTA.
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Clear answers
Questions raised by this field note.
Straightforward guidance for evaluating scope, fit, and the next step.
01What should an AI security checklist include?
Data handling and residency, access control and least privilege, model and prompt security (injection defense, output validation), monitoring and audit logging, incident response, and the vendor's security posture. Clear each before deploying to production.
02What is the biggest AI security risk?
For agentic systems, prompt injection combined with excessive permissions—an attacker hijacks the AI and it acts with more access than it needs. Least privilege, input/output validation, and human approval for high-stakes actions contain it.
03How do I check an AI vendor's security?
Ask where data is processed and stored, how access is controlled and logged, how they defend against prompt injection, their compliance posture for your industry, and how they handle incidents. Vague answers are a warning sign.
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