AI Hacking
AI Security Resources

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

Beginner

Just getting started with AI security? Begin here.

Est. Time: 2-3 weeks

Intermediate

Ready to dive deeper into techniques and tools.

Est. Time: 1-2 months

Advanced

Master-level techniques for experienced practitioners.

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, API Security, 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, Methodology, Statistics

Compliance Officer

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

  • EU AI Act requirements
  • NIST AI RMF implementation
  • Audit checklists
  • Documentation and evidence

Key Pages: Standards, Checklists, Resources

Certifications

AI security certifications and training programs to advance your career.

View Certifications →

Glossary

90 essential terms for AI security professionals.

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 →
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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.

Frequently Asked Questions

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.

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