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12 Security and Ethics

Phase 3 - Systems
Stage 12 of 14. Previous: Stage 11 - Evaluation and Observability. Next: Stage 13 - Production Deployment.

Goal

Learn the main security, privacy, and safety risks in agentic systems.

Learn

Start Here

Security for AI agents is not only about the model refusing unsafe text. Agents read untrusted input, call tools, retrieve documents, store memory, and sometimes change real systems. A safe design treats every step as a security boundary.

Risk Simple Meaning Main Defense
Prompt injection and jailbreaks Hidden or adversarial instructions make the model ignore the intended rules Separate trusted instructions from untrusted content, validate actions, and review high-risk outputs
Insecure output handling Model output is trusted as code, HTML, SQL, commands, or policy decisions Validate, sanitize, encode, and use structured outputs with allowlists
Excessive agency The agent has too much autonomy, tool access, or permission Least privilege, scoped tools, step limits, and human approval
Tool sandboxing and permissions The agent can touch files, networks, commands, or services outside its intended scope Sandboxes, permission policies, audit logs, and approval gates
Data privacy and PII redaction Personal or sensitive data leaks through prompts, logs, memory, or responses Data minimization, redaction, access controls, retention limits, and audits
Bias, toxicity, and guardrails The system produces unfair, abusive, or harmful responses Balanced data, policy filters, evaluation sets, monitoring, and user feedback
Safety and red-team testing Attackers or testers find ways to make the agent fail Repeat adversarial tests before and after release
OWASP LLM Top 10 A production risk map for LLM applications Threat model against each OWASP category

Beginner rule:

Never give an agent more data, permission, autonomy, or trust than the task requires.

Build

Create a threat model and red-team checklist for one agent project. Include prompt injection, insecure output handling, excessive agency, sandbox escape, PII leakage, bias or toxicity, and the OWASP LLM Top 10. Add mitigations for the highest-risk failures.

Exit Criteria

  • You can identify unsafe tool access.
  • You can design human approval for destructive actions.
  • You can test for prompt injection and sensitive data leakage.
  • You can explain why model outputs must be treated as untrusted data.
  • You can map an agent design to the OWASP LLM Top 10 risk categories.

Checkpoint

Use the Stage 12 checkpoint before moving on.