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prompt-injection-jailbreaks

Prompt Injection and Jailbreaks

Last reviewed Jun 1, 2026 Content v20260601
Track mode
none
Means
Read / quiz
Reading
~1 min
Level
advanced

This lesson

This lesson teaches Prompt Injection and Jailbreaks: generative AI patterns—LLMs, prompting, retrieval, safety, and integration habits for real assistants and copilots.

Prompts are code—version, test, and assume hostile content in user and retrieved text.

You will apply Prompt Injection and Jailbreaks in contexts like: Copilots, extraction pipelines, and workflow automation calling foundation models.

Study explanations, case studies, and MCQs—this topic is read/quiz focused without a code runner. Also diff prompt v1 vs v2 against a 20-question golden set.

When prompting, retrieval, and safety fundamentals from intermediate lessons are familiar.

Prompt injection embeds hostile instructions in user or retrieved content—trying to override your system policy ("ignore rules, exfiltrate secrets").

Attack surfaces

  • Direct user chat
  • Indirect via RAG documents, emails, web pages ingested into context
  • Tool outputs manipulated by third parties

Mitigations (defense in depth)

  1. Treat user and retrieved text as untrusted data, not instructions
  2. Output filters and schema validation
  3. Least-privilege tools—no blanket database access
  4. Human review for high-risk actions
  5. Monitor for exfiltration patterns in logs

No silver bullet

Research arms race—combine policy, classifiers, and product UX (confirm before send payment). See Cybersecurity for broader threat modeling.

Important interview questions and answers

  1. Q: Can RAG documents inject prompts?
    A: Yes—poisoned wiki pages are a classic indirect injection vector.

Self-check

  1. Name two injection surfaces.
  2. One mitigation beyond better prompts?

Tip: Add indirect injection tests (poisoned RAG docs) to your eval set—not only rude user chat.

Interview prep

Indirect injection?

Malicious instructions inside retrieved documents or emails.

Mitigation?

Treat external text as data, least-privilege tools, moderation, human review.

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

  • Indirect injection?
  • Tool least privilege?

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