🏗 Securing AI Applications

Learn how modern AI systems are secured using validation, authorization, monitoring, and defense-in-depth principles.

🏦 The Bank Employee Analogy

A bank employee cannot:

• Transfer unlimited money
• Approve everything
• Access every account

Controls exist around the employee.

AI systems require the same approach.

📖 Secure AI Mindset

Never assume:

• AI is always correct
• Input is trustworthy
• Output is safe
• Users behave responsibly

Secure AI starts with healthy skepticism.

🏗 Secure AI Architecture

📥 Input Validation

Before information reaches the model:

• Validate uploads
• Check file types
• Inspect content
• Enforce policies

Security should begin before the model sees data.

🔐 Authorization Controls

One of the biggest mistakes:

Giving AI Access To Everything

AI should only access:

• Required data
• Required tools
• Required systems

Least Privilege still applies.

🛡 What Are Guardrails?

Guardrails are controls around AI systems.

Examples:

• Content Policies
• Access Restrictions
• Approval Workflows
• Response Validation

Guardrails reduce risk when models behave unexpectedly.

📤 Output Validation

Many developers validate inputs.

Few validate outputs.

Questions:

• Is the response safe?
• Is sensitive data included?
• Is the action appropriate?
• Should a human review it?

🤖 AI Agents Need Extra Controls

Agents may:

• Send Emails
• Create Tickets
• Modify Records
• Access Cloud Resources

Higher capability means higher risk.

Additional approval workflows are often necessary.

📊 AI Monitoring

Security teams should track:

• User Activity
• Prompt Activity
• Tool Usage
• Sensitive Data Events
• Agent Actions

Visibility is critical.

📂 Secure RAG Design

Questions architects should ask:

• Who can access documents?
• What documents are indexed?
• How are permissions enforced?
• Can users access unauthorized content?

RAG security is often data security.

👨‍💻 AI Security Architecture Review

• What can users upload?
• What can AI access?
• What tools can AI use?
• What actions can AI perform?
• What logs exist?
• What approvals exist?

These questions should be part of every AI security review.

🏢 SaaS AI Example

Human oversight remains an important security control.

🏆 Key Lesson

The safest AI systems are not the ones that trust the model.

They are the ones that verify everything around the model.

Secure The System
Not Just The Model

🤖 AI Agents & Autonomous Systems

Learn how AI agents work, why they are becoming popular, and what new cybersecurity risks emerge when AI systems can take actions instead of simply generating text.