What You'll Learn
- Understand the unique vulnerabilities of large language models (LLMs) in real-world applications.
- Explore key penetration testing concepts and how they apply to generative AI systems.
- Master the red teaming process for LLMs using hands-on techniques and real attack simulations.
- Analyze why traditional benchmarks fall short in GenAI security and learn better evaluation methods.
- Dive into core vulnerabilities such as prompt injection, hallucinations, biased responses, and more.
- Use the MITRE ATT&CK framework to map out adversarial tactics targeting LLMs.
- Identify and mitigate model-specific threats like excessive agency, model theft, and insecure output handling.
- Conduct and report on exploitation findings for LLM-based applications.
Requirements
- Basic understanding of IT or cybersecurity Curiosity about AI systems and their real-world impact No prior knowledge of penetration testing or LLMs required
Who This Course is For
- SOC Analysts, Security Engineers, and Security Architects aiming to secure LLM systems
- CISO, Security Consultants, and AI Security Consultants seeking to protect AI-driven applications.
- Red Team/Blue Team members and Penetration Testers exploring LLM exploitation and defense techniques.
- Students and tech enthusiasts looking to gain hands-on experience in LLM penetration testing and red teaming.
- Ethical Hackers and Incident Handlers wanting to develop skills in securing generative AI models.
- Prompt Engineers and Machine Learning Engineers interested in securing AI models and understanding vulnerabilities in LLM-based applications.
Your Instructor
Start-Tech Trainings
Analytics and ML academy
4.4 Instructor Rating
8,392 Reviews
192,632 Students
35 Courses
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