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Course Outline
Foundations: Threat Models for Agentic AI
- Types 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 (roles, responsibilities, approval gates)
- Policy design: acceptable use, escalation rules, data handling, and auditability
- Compliance considerations and evidence collection for audits
Non-Human Identity & Authentication for Agents
- Designing identities for agents: service accounts, JWTs, and short-lived credentials
- Least-privilege access patterns and just-in-time credentialing
- Identity lifecycle, 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
- Protecting 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, alerting thresholds, and forensic readiness
- Runbooks and playbooks for agent-related incidents and containment
Red-Teaming Agentic Systems
- Planning red-team exercises: scope, rules of engagement, and safe failover
- Adversarial techniques: prompt injection, tool misuse, chain-of-thought manipulation, and API abuse
- Conducting controlled attacks and measuring 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-deploy safety checks
- Cross-functional governance: security, legal, product, and ops playbooks
Capstone: Red-Team / Blue-Team Exercise
- Execute a simulated red-team attack against a sandboxed agent environment
- Defend, detect, and remediate as the blue team using controls and telemetry
- Present findings, remediation plan, and policy updates
Summary and Next Steps
Requirements
- Solid background in security engineering, system administration, or cloud operations
- Familiarity with AI/ML concepts and large language model (LLM) behavior
- Experience with identity & access management (IAM) and secure system design
Audience
- Security engineers and red-teamers
- AI operations and platform engineers
- Compliance officers and risk managers
- Engineering leads responsible for agent deployments
21 Hours
Delivery Options
Private Group Training
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- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €6840 online delivery, based on a group of 2 delegates, €2160 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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