Description
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.
Red Teaming & Penetration Testing for LLMs is a carefully structured course is designed for security professionals, AI developers, and ethical hackers aiming to secure generative AI applications. From foundational concepts in LLM security to advanced red teaming techniques, this course equips you with both the knowledge and actionable skills to protect LLM systems.
Throughout the course, you’ll engage with practical case studies and attack simulations, including demonstrations on prompt injection, sensitive data disclosure, hallucination handling, model denial of service, and insecure plugin behavior. You’ll also learn to use tools, processes, and frameworks like MITRE ATT&CK to assess AI application risks in a structured manner.
By the end of this course, you will be able to identify and exploit vulnerabilities in LLMs, and design mitigation and reporting strategies that align with industry standards.
Key Benefits for You:
-
LLM Security Insights:
Understand the vulnerabilities of generative AI models and learn proactive testing techniques to identify them. -
Penetration Testing Essentials:
Master red teaming strategies, the phases of exploitation, and post-exploitation handling tailored for LLM-based applications. -
Hands-On Demos:
Gain practical experience through real-world attack simulations, including biased output, overreliance, and information leaks. -
Framework Mastery:
Learn to apply MITRE ATT&CK concepts with hands-on exercises that address LLM-specific threats. -
Secure AI Development:
Enhance your skills in building resilient generative AI applications by implementing defense mechanisms like secure output handling and plugin protections.
Join us today for an exciting journey into the world of AI security—enroll now and take the first step towards becoming an expert in LLM penetration testing!
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.
Reviews
There are no reviews yet.