AI incident response Incident Handling: Lab Series
RCCE students will learn incident response procedures for AI-related security events including AI system compromise, model manipulation, training data breaches, and AI output abuse. RCCE students will learn to identify and classify AI security incidents, apply containment strategies specific to AI systems including model isolation and rollback, collect AI-specific forensic evidence including model versions, training data, and inference logs, investigate root causes of AI incidents, coordinate response efforts between AI engineering, security, and legal teams, develop AI-specific incident response playbooks, and conduct post-incident analysis to improve AI system security. This incident response course prepares students to act decisively during security incidents with structured workflows and clear decision frameworks. At an expert level, RCCE students will learn containment, evidence collection, eradication, and recovery procedures specific to this domain. Students practice incident scenarios that build the composure, coordination, and documentation skills essential for effective incident handling.
- Security Engineers building defensive controls
- Security Analysts and Blue Team members
- Systems Administrators with security responsibilities
- GRC and Risk Professionals supporting controls
- Professionals implementing AI incident response Incident Handling: Lab Series
- Execute hands-on tasks for incident handling
- Execute hands-on tasks for operator edition
- Explain Course Overview fundamentals
- Execute hands-on tasks for focus area
- Execute hands-on tasks for skill level — covering Business Email Compromise response.
- Execute hands-on tasks for bec defined — covering Targeted email fraud exploiting trust.
- Execute hands-on tasks for vendor impersonation
- Execute hands-on tasks for account compromise — covering Urgent wire transfer requests, Changed payment details notice, Credential phishing precedes BEC.
- Execute hands-on tasks for setup → social
- Execute hands-on tasks for engineering → financial
- Execute hands-on tasks for sender policy framework — covering DNS TXT record lists authorized.
- Execute hands-on tasks for domainkeys identified mail — covering DNS TXT record lists authorized.
| Module 01 | Incident Handling |
| Module 02 | Operator Edition |
| Module 03 | Course Overview |
| Module 04 | Focus Area |
| Module 05 | Skill Level |
| Module 06 | BEC Defined |
| Module 07 | Vendor Impersonation |
| Module 08 | Account Compromise |
| Module 09 | Setup → Social |
| Module 10 | Engineering → Financial |
| Module 11 | Sender Policy Framework |
| Module 12 | DomainKeys Identified Mail |
| Module 13 | Anomalous Login Detection for BEC |
| Module 14 | Location: Lagos, Nigeria |
All hands-on labs run on Rocheston Rose X OS. Students practice ai incident response incident handling: lab series by implementing the controls discussed in class, with a focus on real-world deployment, monitoring, and validation.
- Lab 1: Execute hands-on tasks for incident handling
- Lab 2: Execute hands-on tasks for operator edition
- Lab 3: Explain Course Overview fundamentals
- Lab 4: Execute hands-on tasks for focus area
- Lab 5: Execute hands-on tasks for skill level
Upon successful completion of this course, students will receive an official RCCE Course Completion Certificate for AI incident response Incident Handling: Lab Series, verifiable through the Rocheston certification portal.
- Full access to all course materials and slide decks
- Hands-on lab access on Rocheston Rose X OS environment
- Access to Rocheston CyberNotes
- Access to Rocheston Zelfire — EDR/XDR SIEM platform
- Access to Rocheston Raven — online cyber range exercise platform
- Access to Rocheston Vulnerability Vines AI