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gen-ai-security-preview

Generative AI Security (Preview)

Last reviewed May 28, 2026 Content v20260528
Track mode
none
Means
Read / quiz
Reading
~1 min
Level
intermediate

This lesson

This lesson teaches Generative AI Security (Preview): security mindset, common threats, and defensive practices for software teams.

Teams apply Generative AI Security (Preview) in every serious Cybersecurity rollout—skipping it leaves blind spots in reviews and incidents.

You will apply Generative AI Security (Preview) in contexts like: Cloud landing zones and LLM product features with new abuse modes.

Read scenario-based lessons, map controls to code you write on other tracks, and complete MCQs—practice threat modeling on paper or in docs. Also continue on /gen-ai/intro for prompt injection depth.

Toward the end—consolidate compliance preview, interview prep, and production checklist.

LLM features introduce prompt injection, data leakage to vendors, and unsafe tool execution—see Generative AI for depth.

Risks

  • Users paste secrets into chat
  • Retrieved docs contain malicious instructions
  • Agents call APIs with excessive scope

Controls

Data retention policies, output filtering, human approval for payments, least-privilege tools.

Important interview questions and answers

  1. Q: Indirect injection?
    A: Poisoned content in RAG corpus.
  2. Q: Training on customer data?
    A: Read vendor contract and opt-out settings.

Self-check

  1. Name two Gen AI risks.
  2. Name one control.

Tip: Continue on /gen-ai/intro for prompt injection and RAG poisoning.

Interview prep

Prompt injection?

Hostile instructions in user or retrieved content.

Interview tip Lesson completion confidence

Can you explain this lesson in 30 seconds without reading notes?

Not saved yet.

Check yourself

Multiple choice — immediate feedback.

Discussion

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Starter discussion topics

  • Prompt injection?
  • Tool privilege?

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