@nostarch: Practical AI Security by @HarrietHacks comes with 30+ working notebooks so you can learn by doing. Repo is free on her …

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Summary

Harriet Hacks releases a free GitHub repository containing over 30 Jupyter notebooks and Python scripts for learning AI security interactively, accompanying her book 'Practical AI Security'.

Practical AI Security by @HarrietHacks comes with 30+ working notebooks so you can learn by doing. Repo is free on her GitHub. Pairs best with the book. https://github.com/harriethacks/aisecurityhandbook…
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Practical AI Security by @HarrietHacks comes with 30+ working notebooks so you can learn by doing. Repo is free on her GitHub. Pairs best with the book. https://github.com/harriethacks/aisecurityhandbook…


harriethacks/aisecurityhandbook

Source: https://github.com/harriethacks/aisecurityhandbook

👋 Welcome — and thank you for pre-ordering the book!

We’re so excited you’re here! 🎉 This repository contains the example code that accompanies the book, provided as:

📓 Jupyter notebooks (.ipynb) for interactive exploration, and

🐍 Plain Python scripts (.py) for a simpler, no-notebook setup.

Both contain the same core examples — just in different formats.

🚀 How to Run the Examples Option 1 — Open notebooks directly in Google Colab (recommended)

If the example ends in .ipynb, you can run it instantly in Colab:

Find the notebook you want to try. Copy its GitHub URL. Go to Google Colab. Click File → Open notebook → GitHub, then paste the URL. Hit Enter and Colab will open it. Click Runtime → Run all (or press Ctrl + F9).

💡 You can also open notebooks directly using this pattern:

https://colab.research.google.com/github///blob/main/[notebook].ipynb

Example: https://colab.research.google.com/github/harriethacks/aisecurityhandbook/blob/main/wine-analysis.ipynb

Option 2 — Run Python scripts (.py) locally or in Colab

Some examples are provided as .py files instead of notebooks.

You can: Open them in VS Code, or Upload them to Colab and run them like a normal Python script, or Execute them locally from the command line.

To run locally: Clone or download this repository. Make sure you have Python 3.9+ installed.

In a terminal, run:

pip install -r requirements.txt python example_file.py

This option is ideal if you prefer scripts over notebooks or want fewer dependencies.

Option 3 — Run notebooks locally (Jupyter Lab or VS Code)

Clone or download this repository. Install dependencies: pip install -r requirements.txt jupyter lab

Open any .ipynb file and start exploring.

💾 Downloading the Files

Until website integration is live, you can download everything directly from this repo: Code → Download ZIP, or Right-click individual files and choose Save link as…

🧠 What’s Coming Soon

🌐 One-click “Open in Colab” buttons directly from the book’s website

Thank you again for supporting the book and being part of this journey into AI security and systems 💙 Happy experimenting! ⚡

— Harriet

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