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Course Outline

Foundations: Threat Models for Agentic AI

  • Categories of agentic threats: misuse, privilege escalation, data leakage, and supply-chain risks
  • Adversary profiles and attacker capabilities relevant to autonomous agents
  • Mapping assets, trust boundaries, and critical control points for agents

Governance, Policy, and Risk Management

  • Governance frameworks for agentic systems (roles, responsibilities, approval gates)
  • Policy design: acceptable use, escalation rules, data handling, and auditability
  • Compliance considerations and gathering evidence for audits

Non-Human Identity & Authentication for Agents

  • Creating identities for agents: service accounts, JWTs, and short-lived credentials
  • Least-privilege access patterns and just-in-time credentialing
  • Identity lifecycle management: rotation, delegation, and revocation strategies

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
  • Safeguarding sensitive knowledge sources and PII from unauthorized agent access

Observability, Auditing, and Incident Response

  • Designing telemetry for agent behaviour: intent tracing, command logs, and provenance
  • SIEM integration, setting alerting thresholds, and ensuring forensic readiness
  • Runbooks and playbooks for managing agent-related incidents and containment

Red-Teaming Agentic Systems

  • Planning red-team exercises: scope, rules of engagement, and safe failover procedures
  • Adversarial techniques: prompt injection, tool misuse, chain-of-thought manipulation, and API abuse
  • Executing 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, and governance hooks
  • Model and prompt-level defenses: input validation, canonicalization, and output filters

Operationalizing Safe Agent Deployments

  • Deployment patterns: staging, canary, and progressive rollout for agents
  • Change control, testing pipelines, and pre-deployment safety checks
  • Cross-functional governance: security, legal, product, and ops playbooks

Capstone: Red-Team / Blue-Team Exercise

  • Perform a simulated red-team attack against a sandboxed agent environment
  • Defend, detect, and remediate as the blue team using established controls and telemetry
  • Present findings, remediation plans, and proposed policy updates

Summary and Next Steps

Requirements

  • A strong foundation in security engineering, system administration, or cloud operations
  • Proficiency with AI/ML concepts and an understanding of large language model (LLM) behaviour
  • Experience in identity & access management (IAM) and secure system design

Target Audience

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

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