Overview
What is AI Red Teaming?
'Red teaming' is a process where people ethically probe at AI models to find security weaknesses. It's designed to proactively explore an AI system's limits and aims to strengthen its defenses or raise awareness of potential misuse.
Who cares?
AI is not perfect yet. It's nowhere near.
As AI models evolve at an exponential rate, allowing billions of people to harness the power of it, we don't know the harm that it could cause.
Many people use AI without understanding the knowledge of how it works, how it functions, the frameworks, etc. There is a potential for major misuse for the people that understand how models function at an internal level: abusing the weak security metrics imposed on even the highest level of AI models that function right now, including ChatGPT, Claude, and Gemini.
As these top-end models have red teamers solving issues and research studies constantly finding top-notch security protocols, it's simply not fast enough for hackers to find new metrics of breaching defenses.
The Contents
Below is a list of all of the chapters that will be discussed within the publication:
I. Prompt Engineering
II. Jailbreaking
III. Evolution of AI Vulnerabilities
IV. Manipulation
V. Extracting Model Secrets
VI. Large Language Models: Attacks & Defenses
VII. Advanced Defenses
VIII.. Memory Injections
IX. Special Handling & Edge Cases
X. Code Analysis
XI. Image Generation
XII. Deepfaking
XIII. Future Threats
Each chapter discusses real-world scenarios for attacks, defensive countermeasures, and loopholes behind them.
