Get in Touch

Course Outline

Foundations: Threat Models for Agentic AI

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

Governance, Policy, and Risk Management

  • Governance frameworks for agentic systems, including roles, responsibilities, and approval gates
  • Policy design covering acceptable use, escalation rules, data handling, and auditability
  • Compliance considerations and evidence collection for audits

Non-Human Identity and Authentication for Agents

  • Designing agent identities: service accounts, JWTs, and short-lived credentials
  • Least-privilege access patterns and just-in-time credentialing
  • Strategies for identity lifecycle management, 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 principles
  • Safeguarding sensitive knowledge sources and PII from unauthorized agent access

Observability, Auditing, and Incident Response

  • Designing telemetry for agent behavior, including intent tracing, command logs, and provenance
  • SIEM integration, alerting thresholds, and forensic readiness
  • Runbooks and playbooks for handling 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 filters

Operationalizing Safe Agent Deployments

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

Capstone: Red-Team / Blue-Team Exercise

  • Executing a simulated red-team attack against a sandboxed agent environment
  • Defending, detecting, and remediating as the blue team using established controls and telemetry
  • Presenting findings, remediation plans, and proposed policy updates

Summary and Next Steps

Requirements

  • A solid foundation in security engineering, system administration, or cloud operations
  • Familiarity with AI/ML concepts and the behavior of large language models (LLMs)
  • Experience with identity and access management (IAM) and secure system design

Audience

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

Number of participants


Price per participant

Testimonials (1)

Upcoming Courses

Related Categories