Ethical Hacking LLMs

Roles:

• Engineering Students

• Industry Professional Software Engineers

• AI Engineers

• Cybersecurity Engineers

• AI Security Engineers

Summary:

Deploy, attack, and defend LLM-based systems in simulated environments. Learn real-world AI security practices, prompt injection, data exfiltration, and threat modeling for large language models.

Details:

• Duration: 3 days

• Level: Intermediate

• Format: Virtual / On-site

• Labs: Yes

• Certification: Included

Overview:

This course introduces participants to the ethical hacking and security of LLMs. You will gain hands-on experience with attack and defense strategies, secure prompt pipelines, and AI system hardening. By the end of this course, you will be able to identify and mitigate threats to LLM-powered services in cloud and data center environments.

The course is project-based and interactive, ensuring learners stay engaged while completing real-world simulations that mirror industry practices.

What You’ll Learn:

• Threat modeling for LLM apps (prompt injection, data exfiltration, jailbreaks)

• Secure prompt/response pipelines and guardrails

• Secrets, tokens, and key rotation in cloud KMS

• Network policies & egress filtering for model I/O

• Monitoring: model misuse, drift, anomaly alerts

• Incident response runbooks for AI services

• Hands-on attack/defense labs for LLMs

Technologies Used:

• LLM Platforms (OpenAI, HuggingFace)

• Kubernetes & Istio

• NVIDIA GPUs

• Cloud KMS (AWS, GCP, Azure)

• Open-source AI guardrails

Target Audience:

• Engineering students interested in AI security

• Software engineers working with AI/ML systems

• AI engineers deploying LLMs

• Cybersecurity professionals focusing on AI infrastructure

• AI security engineers

Prerequisites:

• Python fundamentals

• Basic Kubernetes and cloud knowledge

Syllabus :

1. Introduction to Ethical Hacking for LLMs

2. Threat Modeling & Attack Vectors

3. Secure Prompt Pipelines & Guardrails

4. Secrets, Tokens & Key Management

5. Network Policies & Egress Controls

6. Monitoring & Incident Response

7. Capstone Lab: Attack & Defend an LLM Deployment

Capstone Lab & Assessment:

• Simulate attacks on a deployed LLM system

• Implement defense strategies

• Complete a final assessment to validate learning