AI/ML Security Threats: TryHackMe Solutions

AI/ML Security Threats

Artificial Intelligence (AI) is rapidly transforming every industry — and cybersecurity is no exception. As AI becomes a core topic in security discussions, it’s vital to understand what AI and Machine Learning (ML) are, how they’re used, and how they impact both defenders and attackers. This lab explores the fundamentals of AI in cybersecurity, the opportunities it brings, and the risks it introduces.

Task 1 Introduction

1 I’m ready to learn about AI/ML security threats!

No answer needed

Task 2 The Building Blocks of AI

1 What category of machine learning combines both labelled and unlabelled data?

semi-supervised learning

2 What is the first layer in a neural network that handles incoming raw data?

input layer

3 Which learning method does not require human-labeled data and can extract features from raw, unstructured input?

deep learning

4 What are the weighted connections between nodes in a neural network meant to simulate in the human brain?

synapses

Task 3 LLMs

1 What type of AI model enabled major advancements in ChatGPT and similar tools?

large language models

2 What is the first training stage where an LLM processes massive amounts of data?

pre-training

3 What type of neural network introduced by Google in 2017 powers modern LLMs?

transformer

Task 4 AI Security Threats

1 What framework was developed by MITRE to guide the understanding of AI-specific cyber threats?

ATLAS

2 What type of attack involves cloning an AI model by interacting with its API?

model theft

3 What generative AI technique can replicate a person’s voice or appearance with high realism?

deepfake

4 What common social engineering attack has become harder to detect due to AI-generated fluent and convincing messages?

phishing

Task 5 Defensive AI

1 According to IBM, how many days faster does AI help identify and contain breaches?

108

2 What cybersecurity task benefits from AI helping to imagine attacker behavior we might not consider?

threat hunting

3 Explainability tools such as SHAP and LIME help with what?

model monitoring

Task 6 Practical

1 What’s the flag?

thm{443/60/16384}

Task 7 Conclusion

Artificial Intelligence (AI) enables machines to mimic human behavior.

• Machine Learning (ML) trains models to make predictions from data.
• Deep Learning (DL), a subset of ML, uses neural networks to process data without human input.
• DL powers technologies like LLMs, which understand and respond to natural language.

AI can enhance cyberattacks (e.g., phishing) but also defend against them. To be effective and safe, AI must be adopted securely, without introducing new vulnerabilities.