The AI Hacking 101 ILT teaches students the fundamentals of penetration testing AI/LLM based applications such as customer facing chatbots.
The course focuses on demonstrating how to detect and exploit common AI vulnerabilities such as:
Prompt Injection
Sensitive Information Disclosure
Improper Output Handling
System Prompt Leakage
Misinformation
Excessive Agency
Not only will students learn about these exploits, but they will also spend hands-on time in a custom-built environment exploiting and uncovering these vulnerabilities. The online lab features the TCM Vulnerable Chatbot, a customer service chatbot that can interact with customers’ tickets and improve its responses via Retrieval Augmented Generation (RAG) using the company’s knowledge base.
Course Outline
1 – AI Fundamentals Review
A quick review of some of the fundamentals of AI such as how they operate and standard terms such as model parameters, temperature, top-p, inference, training, LLMs.
2 – AI Threat Model
Discuss the threat actors, assets, adversary goals and attack surfaces for modern AI applications and the specific AI application used in the course
3 – Reconnaissance, Model Mapping and Baseline Behavior and Fingerprinting
Demonstrate techniques for performing reconnaissance of AI applications with a specific focus on fingerprinting underlying AI models and their settings.
4 – Prompt Injection and Jailbreaking
Demonstrate common techniques for prompt injection and jail breaking
5 – Prompt Injection Tools and Resources
Show common tools and repositories of prompts used for prompt injection and jailbreaking
6 – Bypassing Common Protections
Showcase how to bypass common protections for prompt injection such as input/output filtering
7 – Testing for harmful output/hate speech/misinformation/off-topic content and resource drainage
Demonstrate tests for verifying the model responds correctly to requests for generating harmful or Off-topic content or attempts to waste resources.
8 – Data Exfiltration
Demonstrate how retrieval augmented generation works and vulnerabilities associated with it such as leakage of confidential material and PII.
9 – RAG and Vector DB Attacks
Demonstrate attacks the focus on the retrieval of documents and the ticket base, showcase vector poisoning attacks.
10 – Excessive Agency
Demonstrate how excessive agency in applications can be exploited and tested for.