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AI Security Laboratory: Hands-On + Full-Stack (Lifetime Lab Access)

live online
price $1,400
Dawid
Intermediate
2 Days
AI Focus
Wed 9 Dec - Thu 10 Dec
price $1,400
Register


Online, Available in English

Topics:

  • Prompt injection: direct and indirect 
  • LLM jailbreaking 
  • Fuzzing LLM applications
  • AI-powered shell
  • Advanced prompting
  • Local LLMs / Private AI
  • AI programming
  • AI attack detection
  • OpenAI models and API
  • Embeddings
  • Quantization
  • LLM Guard
  • Building agentic AI 
  • Creating your own prediction model
  • CVE research / PoC development with AI
  • Smarter AI assessing other AI
  • Specialized AI security tools
     


Overview

AI has introduced an entirely new layer of security risk — one that needs to be understood from both attacker and builder perspectives. This training is a hands-on, full-stack guide to that landscape, showing how modern AI systems are attacked, built, and used in real-world security.

You will work through the offensive side of AI security with prompt injection, jailbreaking, and fuzzing of LLM applications. You will also apply AI in security engineering and daily operations — turn AI building blocks into practical workflows and use AI security tools for everyday tasks.

Along the way, you will move into more advanced capabilities — building agentic AI for real-time security operations, applying AI to vulnerability research and PoC development, and exploring how smarter AI can assess other AI.

The training includes hands-on exercises, reusable Python scripts, and lifetime lab access — so you can continue practicing and applying what you learned long after the class ends.

Students will be given a VMware image with a specially prepared lab environment to work on many topics and exercises in this training. When the training is over, students can take the lab environment home (after signing a non-disclosure agreement) to continue practicing at their own pace.

 

By the end of this course, the participant will be able to:

  • Master AI attack vectors like prompt injection
  • Build secure workflows with both local and cloud LLMs 
  • Implement defenses using LLM Guard, fuzz non-deterministic models, and automate daily security tasks with practical Python scripts