Red teaming and adversarial testing in Prompt Engineering / GenAI - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is red teaming in the context of AI?

Red teaming is a process where experts simulate attacks or challenges on an AI system to find weaknesses before bad actors do.

beginner

What does adversarial testing aim to do?

Adversarial testing tries to find inputs that confuse or trick an AI model, revealing its vulnerabilities.

intermediate

Why is red teaming important for AI safety?

It helps catch hidden problems early, making AI systems safer and more reliable before they are widely used.

beginner

Give an example of an adversarial input.

An image slightly changed so a model mistakes a cat for a dog is an adversarial input.

intermediate

How do red teaming and adversarial testing differ?

Red teaming is broader, including many attack types and strategies, while adversarial testing focuses on tricky inputs to fool models.

What is the main goal of red teaming in AI?

A To find and fix AI weaknesses before real attacks happen

B To train AI models faster

C To collect more data for AI

D To improve AI user interface

Red teaming aims to find and fix weaknesses in AI systems before attackers exploit them.

Which of these is an example of adversarial testing?

A Increasing training data size

B Changing input data slightly to confuse the AI

C Adding more layers to a neural network

D Deploying AI to production

Adversarial testing involves modifying inputs to trick or confuse AI models.

Why might an AI system fail when given adversarial inputs?

A Because the inputs exploit model weaknesses

B Because the AI is too slow

C Because the AI has too much data

D Because the AI is overfitting

Adversarial inputs are designed to exploit weaknesses in AI models causing failures.

Which activity is NOT part of red teaming?

A Simulating attacks on AI

B Testing AI with tricky inputs

C Improving AI user experience design

D Finding security gaps

Improving user experience is not part of red teaming, which focuses on security and robustness.

What is a key benefit of adversarial testing?

A It improves AI hardware

B It speeds up AI training

C It reduces AI model size

D It reveals hidden AI vulnerabilities

Adversarial testing helps find hidden vulnerabilities by challenging AI with tricky inputs.

Explain in your own words what red teaming is and why it matters for AI systems.

Think about how experts try to 'attack' AI to make it stronger.

Describe what adversarial testing involves and give a simple example.

Imagine changing a picture just a little to fool an AI.