Learn how modern AI systems are attacked, secured, built, and applied to real-world security operations through an intensive hands-on laboratory experience.
AI Security Laboratory Hands-On + Full-Stack is a two-day immersive training program focused on the new layer of security risk introduced by modern artificial intelligence systems.
The course approaches AI security from both the attacker and builder perspectives. Participants explore how Large Language Model applications can be exploited while also learning how AI systems can be designed, protected, and used effectively in day-to-day security engineering and operations.
On the offensive side, the course covers current attack techniques such as prompt injection, LLM jailbreaking, and fuzzing of LLM applications. Participants explore attack surfaces that differ significantly from traditional applications and examine how the non-deterministic behavior of modern models changes security testing methodologies.
The defensive and engineering sections introduce local LLMs, private AI architectures, data anonymization workflows, AI attack detection, and open-source protection technologies such as LLM Guard.
The course then moves into more advanced capabilities, including building agentic AI systems for real-time security operations, using AI for vulnerability and CVE research, developing proofs of concept, and exploring techniques in which more capable AI systems are used to assess other AI systems.
Hands-on exercises are supported by reusable Python scripts and lifetime laboratory access, allowing participants to continue experimenting and applying the techniques after the course.
Training Format
This is a two-day, hands-on, full-stack AI security laboratory.
The course combines offensive security, defensive engineering, AI development, and security automation rather than treating them as isolated subjects.
Benefits for Organizations
As AI systems become more common in production environments, organizations face security risks that extend beyond traditional application security controls.
This training can help technical teams:
- Understand AI-specific attack surfaces,
- Assess prompt injection and jailbreaking risks,
- Develop AI-focused guardrails and defence mechanisms,
- Handle sensitive information more safely in AI workflows,
- Introduce AI automation into SOC and security engineering operations,
- Integrate AI systems into production environments with a stronger security perspective.
Benefits for Participants
After completing the course, participants will be able to approach AI security from a full-stack perspective that includes offensive testing, defensive engineering, AI development, and security operations.
Participants will gain practical experience to:
- Test LLM-powered applications for AI-specific attacks.
- Identify emerging AI vulnerability classes.
- Build local and cloud-based LLM security workflows.
- Apply defensive layers and AI guardrails.
- Develop reusable Python automation for security activities.
- Use AI to support vulnerability research.
- Adapt agentic AI systems to security operations use cases.
- Continue practicing after the course through lifetime laboratory access.
