9.1 LLM and Agent Security¶

Role at Stage 9: AI Security, Blockchain, and ZKML¶

Protect systems where models read untrusted content and call tools. This part is one capability inside the stage. It should leave behind an artifact, measurements, and a short explanation of failure modes.

Explanation¶

This part has 4 sub-parts because the topic needs that many learning units to feel natural. Some stages have more parts and some have fewer; the structure follows the topic, not a fixed template.

Part Diagram¶

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flowchart LR
  P["<b>9.1</b><br/>LLM and Agent Security"]
  P --> S1["<b>9.1.1</b><br/>Prompt Injection and<br/>Jailbreaks"]
  P --> S2["<b>9.1.2</b><br/>Tool Injection and<br/>Excessive Agency"]
  P --> S3["<b>9.1.3</b><br/>Data Leakage and<br/>Prompt Logs"]
  P --> S4["<b>9.1.4</b><br/>Insecure Output<br/>Handling"]
  P --> E["<b>Exam</b><br/>Part practice"]

Sub-Parts¶

Sub-part folder	What it explains
9.1.1 Prompt Injection and Jailbreaks	Prompt Injection and Jailbreaks is the working skill inside LLM and Agent Security that helps you build the stage artifact, A threat model, red-team report, smart contract security lab, and tiny ZKML or verifiable computation demo, while collecting enough evidence to trust the result.
9.1.2 Tool Injection and Excessive Agency	Tool Injection and Excessive Agency is the working skill inside LLM and Agent Security that helps you build the stage artifact, A threat model, red-team report, smart contract security lab, and tiny ZKML or verifiable computation demo, while collecting enough evidence to trust the result.
9.1.3 Data Leakage and Prompt Logs	Data Leakage and Prompt Logs is the working skill inside LLM and Agent Security that helps you build the stage artifact, A threat model, red-team report, smart contract security lab, and tiny ZKML or verifiable computation demo, while collecting enough evidence to trust the result.
9.1.4 Insecure Output Handling	Insecure Output Handling is the working skill inside LLM and Agent Security that helps you build the stage artifact, A threat model, red-team report, smart contract security lab, and tiny ZKML or verifiable computation demo, while collecting enough evidence to trust the result.

What a Person Who Masters This Part Can Do¶

Explain how LLM and Agent Security supports a threat model, red-team report, smart contract security lab, and tiny zkml or verifiable computation demo..
Build and inspect this artifact: Threat-model the Stage 6 agent.
Measure progress with: Track attacks, blocked actions, exposure, and residual risks.
Debug at least one failure mode before moving to the next part.

Build and Measure¶

Build: Threat-model the Stage 6 agent.

Measure: Track attacks, blocked actions, exposure, and residual risks.

Tests¶

Take one 30-question exam after studying this part. It opens in a new browser tab so the study page stays available.

Open Part Exam

Back to Stage¶

Return to Stage 9: AI Security, Blockchain, and ZKML.