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Course Outline

Foundations: Threat Modeling for Agentic AI

  • Categories of agentic threats: misuse, escalation, data leakage, and supply-chain vulnerabilities.
  • Adversary profiles and attacker capabilities relevant to autonomous agents.
  • Mapping assets, trust boundaries, and key control points for agent systems.

Governance, Policy, and Risk Management

  • Governance frameworks for agentic systems, including roles, responsibilities, and approval gates.
  • Crafting policies: acceptable use, escalation rules, data handling, and auditability.
  • Compliance considerations and gathering evidence for audits.

Non-Human Identity & Authentication for Agents

  • Architecting agent identities: service accounts, JWTs, and short-lived credentials.
  • Implementing least-privilege access patterns and just-in-time credentialing.
  • Managing identity lifecycle, rotation, delegation, and revocation.

Access Controls, Secrets, and Data Protection

  • Fine-grained access control models and capability-based patterns for agents.
  • Secrets management, encryption in transit and at rest, and data minimization strategies.
  • Safeguarding sensitive knowledge sources and PII from unauthorized agent access.

Observability, Auditing, and Incident Response

  • Designing telemetry for agent behavior: intent tracing, command logs, and provenance.
  • SIEM integration, setting alerting thresholds, and ensuring forensic readiness.
  • Developing runbooks and playbooks for agent-related incidents and containment.

Red-Teaming Agentic Systems

  • Planning red-team exercises: defining scope, rules of engagement, and safe failover procedures.
  • Adversarial techniques: prompt injection, tool misuse, chain-of-thought manipulation, and API abuse.
  • Conducting controlled attacks to measure exposure and impact.

Hardening and Mitigations

  • Engineering controls: response throttles, capability gating, and sandboxing.
  • Policy and orchestration controls: approval flows, human-in-the-loop mechanisms, and governance hooks.
  • Model and prompt-level defenses: input validation, canonicalization, and output filtering.

Operationalizing Safe Agent Deployments

  • Deployment strategies: staging, canary releases, and progressive rollouts for agents.
  • Change control, testing pipelines, and pre-deployment safety checks.
  • Cross-functional governance: playbooks for security, legal, product, and ops teams.

Capstone: Red-Team / Blue-Team Exercise

  • Execute a simulated red-team attack on a sandboxed agent environment.
  • Defend, detect, and remediate as the blue team using established controls and telemetry.
  • Present findings, a remediation plan, and recommended policy updates.

Summary and Next Steps

Requirements

  • Robust experience in security engineering, system administration, or cloud operations.
  • Working knowledge of AI/ML concepts and the behavior of large language models (LLMs).
  • Proficiency in identity & access management (IAM) and secure system design principles.

Target Audience

  • Security engineers and red-team specialists.
  • AI operations and platform engineers.
  • Compliance officers and risk management professionals.
  • Engineering leads overseeing agent deployments.
 21 Hours

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