Security: Protect Your AI Systems

AI systems are uniquely vulnerable. Prompt injection, data leakage, and adversarial attacks require new security thinking. This track covers the threats and defenses specific to LLM applications.

🎯 What You’ll Master

Prompt Injection Defense

Understand and defend against prompt injection attacks. Build multi-layer defenses that don’t break usability.

Data Protection

Detect and redact PII, prevent data leakage, and ensure compliance with privacy regulations.

AI Firewall

Implement input/output filtering, rate limiting, and anomaly detection for production LLMs.

Shadow AI Audit

Discover unauthorized AI usage in your organization and bring it under governance.

🛡️ Prompt Injection Defense

Prompt Injection 101 Understand the threat

Injection Attack Taxonomy Attack types & examples

Input Sanitization First line of defense

Prompt Armor Patterns Defense-in-depth

Output Validation Catch injection effects

🔒 Data Protection

PII Detection & Redaction Automatic sensitive data handling

Data Leakage Prevention Prevent training data extraction

Compliance Frameworks GDPR, HIPAA, SOC2 for AI

🏰 Infrastructure Security

AI Firewall Architecture Gateway security layers

Rate Limiting & Abuse Prevention Protect from attack floods

Model Access Control Who can use what

Audit Logging Security event tracking

🔍 Governance & Discovery

Shadow AI Audit Find unauthorized usage

AI Risk Assessment Evaluate and mitigate risks

🚀 Quick Wins

Add input length limits → Block many injection attempts
Implement PII detection → Catch leaks before they happen
Audit API key usage → Find shadow AI immediately
Add output filtering → Defense-in-depth

Coming Soon: Prompt Injection Playground

Our interactive prompt injection testing environment is under development.