How do I start learning AI security?

Start with foundational knowledge of LLM architecture and common vulnerabilities (OWASP LLM Top 10). Practice with hands-on labs like OWASP's AI security challenges, Hack The Box's AI modules, and local LLM testing with tools like Ollama. Follow structured learning paths that cover prompt injection, red teaming, and secure AI development.

What are the best AI security certifications available?

Top AI security certifications include: AI Security Certified Professional (AISCP), Certified AI Security Professional (CAISP), CEH with AI security specialization, and SANS AI security courses. These certifications cover LLM security testing, adversarial machine learning, and AI risk management frameworks.

What learning path should I follow for AI red teaming?

An AI red teaming learning path includes: 1) Master prompt injection techniques and jailbreaking, 2) Learn MCP server security testing, 3) Study model extraction and inversion attacks, 4) Practice with tools like Garak and PyRIT, 5) Understand agentic AI vulnerabilities and OWASP Agentic Top 10.

What are the best resources for learning LLM security?

Best LLM security resources include: OWASP LLM Top 10 and Agentic Top 10 guides, AI Hacking Portal's comprehensive testing methodology, NIST AI RMF documentation, MITRE ATLAS knowledge base, and Capture The Flag challenges like the OWASP FinBot CTF for hands-on agentic AI security practice.

AI Security Learning Center

Structured learning paths, certifications, and community resources to build your AI security expertise — whether you are a red teamer, developer, analyst, or compliance professional.

Skill Levels

Principiante

Just getting started with AI security? Begin here.

Glossario sulla sicurezza AI — Learn the terminology
OWASP LLM Top 10 — Understand the risk landscape
Prompt Injection Basics — The #1 vulnerability explained
Testing Methodology Overview — How AI pentesting works

Est. Time: 2-3 weeks

Intermedio

Ready to dive deeper into techniques and tools.

RAG Security Deep Dive — Vector DB attacks, poisoning
Guida alla sicurezza MCP — Model Context Protocol vulnerabilities
AI Pentesting Tools — Garak, PyRIT, LLM Guard hands-on
Security Checklists — Apply structured testing

Est. Time: 1-2 months

Avanzate

Master-level techniques for experienced practitioners.

Red Teaming Methodology — Full adversarial engagement
Sicurezza dell'intelligenza artificiale — Autonomous agent threat modeling
Multimodal Attacks — Vision, audio, cross-modal
Incident Response — Breach response and forensics

Est. Time: 3+ months

Career Learning Paths

Red Teamer

Focus: Offensive AI security testing, vulnerability discovery, and exploitation.

Prompt injection mastery
RAG and MCP exploitation
Tool development (Garak, PyRIT)
Report writing and PoC creation

Key Pages: Red Teaming, Tools, Incidents

AI Developer

Focus: Building secure AI applications with defensive patterns.

Secure coding patterns
Input/output validation
API security design
CI/CD security integration

Key Pages: Secure Dev, Sicurezza API, Development

Security Analyst

Focus: Threat assessment, monitoring, and risk analysis for AI systems.

Threat modeling for AI
Vulnerability assessment
Log analysis and anomaly detection
Risk scoring and reporting

Key Pages: Threats, Metodologia, Statistics

Compliance Officer

Focus: Regulatory compliance, audit, and governance for AI deployments.

Requisiti della legge sull'intelligenza artificiale dell'UE
NIST AI RMF implementation
Audit checklists
Documentation and evidence

Key Pages: Standards, Checklists, Resources

Certificazioni

Certificazioni di sicurezza AI e programmi di formazione per far avanzare la tua carriera.

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Glossario

Oltre 100 termini essenziali per i professionisti della sicurezza AI.

Browse Terms →

Resources

Additional resources, tools, and references.

View Resources →

CTF Challenges

Practice hands-on with the OWASP FinBot CTF for agentic AI security testing.

Play FinBot CTF →

AI Hacking Team

The AI Hacking team researches and documents AI/LLM security vulnerabilities, red teaming techniques, and defensive strategies. Our guides are based on real-world pentesting experience and continuous monitoring of the AI security landscape.

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