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MICRO-COURSE

AI Security

AI Security: 10 short lessons, one for each concept. Prompt injection, untrusted retrieved content, sensitive-data exposure, excessive tool permissions, insecure output handling, model extraction risks, supply-chain risks, sandboxing, approval boundaries, and auditability.

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01 / WATCH

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02 / UNDERSTAND

Start with the topic guide.

Prompt injection, untrusted retrieved content, sensitive-data exposure, excessive tool permissions, insecure output handling, model extraction risks, supply-chain risks, sandboxing, approval boundaries, and auditability.

This is a learning outline. A complete worked tutorial has not been published for this topic yet.

01

Concept scope

AI Security: 10 short lessons, one for each concept. Prompt injection, untrusted retrieved content, sensitive-data exposure, excessive tool permissions, insecure output handling, model extraction risks, supply-chain risks, sandboxing, approval boundaries, and auditability.

03 / TRY IT

Prepare a focused example

  1. Choose one question about AI Security that you want to answer.
  2. Write down a small example, its inputs or starting point, and the result you expect.
  3. Explain your reasoning and note what you would like reviewed in a live or 1:1 session.
Keep your work

A short example, reasoning and an open question

Check your understanding

  • Explain the concept in your own words and identify where it fits in the subject.
  • Show one small example, the expected result and the reasoning behind it.
  • Record one limitation or edge case and a question to discuss with a mentor.
04 / LEARN WITH HELP

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