Lilly Tech Systems
LLM Security Fundamentals
Comprehensive security training for LLM-powered applications. Master the OWASP LLM Top 10, build threat models, secure inputs and outputs, protect AI agents, and implement production monitoring.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
The LLM security landscape, OWASP LLM Top 10 overview, and why LLM security requires a new approach.
2. Attack Surface
Comprehensive LLM threat model covering inputs, outputs, training data, model weights, tools, and infrastructure.
3. Prompt Attacks
Direct injection, indirect injection, jailbreaking, prompt leaking, and multi-turn attack strategies.
4. Data Leakage
Training data extraction, PII exposure, system prompt leakage, and sensitive information disclosure.
5. Agent Security
Tool use risks, privilege escalation, multi-agent vulnerabilities, and securing autonomous AI systems.
6. Monitoring
Production monitoring, anomaly detection, audit logging, and real-time security alerting for LLM systems.
7. Best Practices
Security-first architecture, defense checklists, compliance, and building a security culture for AI teams.
What You'll Learn
By the end of this course, you'll be able to:
Map LLM Threats
Build comprehensive threat models for LLM applications covering all attack vectors from the OWASP LLM Top 10.
Secure I/O Pipelines
Implement input validation, output filtering, and content safety systems for production LLM deployments.
Protect AI Agents
Secure tool-using AI agents against privilege escalation, confused deputy attacks, and autonomous action risks.
Monitor and Respond
Deploy monitoring systems that detect security incidents, anomalies, and abuse patterns in LLM applications.