BeginnerCybersecurity for AI
AI Security Essentials
Day 1 of the intensive teaches defenders how GenAI and LLM apps are attacked. Map new AI threat surfaces, apply OWASP LLM Top 10 mitigations, and build threat models that drive pragmatic controls.
Prerequisites
- Basic programming in Python or Java
- Comfort working with APIs
- High-level familiarity with cybersecurity concepts
Who Should Attend
- Data Scientists
- ML Engineers
- Research Engineers building production models
- Career changers entering the AI field
- Anyone with basic technical literacy
Course Outline
- 1AI vs. traditional security mindsets and emergent vulnerabilities
- 2Mapping AI attack surfaces: training data, embeddings, APIs, model endpoints
- 3OWASP Top 10 for LLM Applications deep dive and mitigation labs
- 4Foundational AI threat modeling with STRIDE-AI
- 5Zero-trust guardrails for GenAI workloads
- 6Monitoring and anomaly detection for AI pipelines
Learning Outcomes
- Explain why AI workloads expand the classic attack surface
- Apply OWASP LLM Top 10 mitigations to live systems
- Produce an actionable threat model for an AI product
- Recommend guardrails for input/output filtering
- Instrument monitoring to catch anomalous AI behavior
Related Courses
Intermediate
Prompt Hacking & GenAI Defense
Day 2 turns security teams into red-teamers. Execute real prompt-injection, jailbreak, and RAG exploits, then design layered guardrails, content safety filters, and monitoring pipelines to stop them in production.
Advanced
Agentic AI Security & Governance
Day 3 focuses on securing autonomous, tool-using AI agents at enterprise scale. Architect zero-trust controls, map threats with MITRE ATLAS & STRIDE-AI, and align deployments with EU AI Act, NIST RMF, and ISO 42001.
Ready to Get Started?
Contact us to schedule training for your team or inquire about upcoming sessions.