Certified Agentic Artificial Intelligence Cyber Investigator (CAAICI) Certification Program by Tonex
The Certified Agentic Artificial Intelligence Cyber Investigator (CAAICI) Certification Program by Tonex prepares professionals to investigate cyber incidents involving autonomous and semi-autonomous Artificial Intelligence systems. The program examines how agentic Artificial Intelligence operates, how digital evidence may be generated or altered by autonomous agents, and how investigators can evaluate actions, decisions, communications, tool use, and system interactions across complex environments.
Participants learn investigative methods for identifying suspicious agent behavior, reconstructing event timelines, analyzing prompts and execution traces, examining identity and access activity, evaluating data movement, and documenting findings for technical and management audiences. The program uses a practical training approach that includes exercises, real-world case studies, and examples of processes and documentation used in agentic Artificial Intelligence cyber investigation projects.
Cybersecurity is central to investigating autonomous agents because compromised or misaligned systems may perform actions at machine speed across interconnected environments. Strong cybersecurity investigation practices help professionals identify malicious activity, establish evidence integrity, determine scope and impact, and support effective containment, remediation, governance, and accountability.
Learning Objectives
Upon successful completion of this program, participants will be able to:
- Explain agentic Artificial Intelligence architectures, behaviors, workflows, and security implications.
- Identify evidence sources associated with autonomous agents, tools, identities, and connected systems.
- Reconstruct cyber incident timelines involving prompts, actions, communications, and system events.
- Analyze agent decisions, permissions, data access, and interactions with external resources.
- Apply investigative methods for attribution, evidence preservation, root-cause analysis, and reporting.
- Evaluate cybersecurity risks involving compromised, manipulated, or improperly governed Artificial Intelligence agents.
- Produce defensible investigation findings and recommendations for technical, legal, and management stakeholders.
Audience
This certification program is designed for:
- Cybersecurity Professionals
- Digital Forensics Investigators
- Cyber Incident Response Professionals
- Security Operations Center Analysts
- Threat Intelligence Analysts
- Artificial Intelligence Security Professionals
- Cloud Security Professionals
- Security Engineers
- Governance, Risk, and Compliance Professionals
- Internal Audit and Assurance Professionals
- Law Enforcement and Investigative Personnel
- Artificial Intelligence Governance and Risk Leaders
Program Modules
Module 1: Agentic Artificial Intelligence Investigation Foundations
- Agentic Artificial Intelligence concepts and operational models
- Autonomous and semi-autonomous agent characteristics
- Agent goals, planning, reasoning, and execution
- Human oversight and delegated authority
- Investigation objectives and evidence requirements
- Common agentic Artificial Intelligence security incidents
- Investigative ethics and professional responsibilities
Module 2: Digital Evidence Collection and Preservation
- Agent logs and activity records
- Prompt and response evidence collection
- Tool invocation and execution records
- Identity and access evidence sources
- Cloud and application event records
- Evidence preservation and chain of custody
- Documentation for defensible investigations
Module 3: Agent Behavior and Timeline Analysis
- Event sequencing and timeline reconstruction
- Agent decision and action correlation
- Prompt history and instruction analysis
- Task execution and tool usage review
- Data access and movement analysis
- Anomalous behavior identification techniques
- Root-cause and impact determination
Module 4: Threat Attribution and Compromise Investigation
- Malicious agent activity indicators
- Credential misuse and privilege escalation
- Prompt injection and instruction manipulation
- Unauthorized tool and application access
- Adversarial control and agent hijacking
- Threat actor behavior and attribution considerations
- Compromise scope and persistence assessment
Module 5: Incident Response and Evidence Reporting
- Investigation triage and prioritization
- Containment and evidence preservation coordination
- Incident scoping and affected asset identification
- Findings validation and investigative confidence
- Technical report development practices
- Executive and stakeholder communication
- Remediation and lessons-learned documentation
Module 6: Governance Security and Investigation Assurance
- Agentic Artificial Intelligence governance requirements
- Identity, access, and permission oversight
- Logging and monitoring governance
- Cybersecurity controls for autonomous systems
- Investigation quality and evidence assurance
- Regulatory and organizational accountability
- Continuous improvement of investigation processes
Exam Domains
- Autonomous Agent Architecture and Security Concepts
- Cyber Evidence Acquisition and Integrity Management
- Behavioral Reconstruction and Digital Trace Analysis
- Adversarial Activity and Compromise Attribution
- Incident Investigation Reporting and Response Coordination
- Artificial Intelligence Governance and Investigative Assurance
Course Delivery
The course is delivered through a combination of lectures, interactive discussions, hands-on workshops, case-based exercises, and project-based learning facilitated by experts in Artificial Intelligence security, cyber investigations, digital forensics, and incident response. Participants will have access to readings, case studies, investigative frameworks, and tools for practical exercises.
The program uses a practical training approach that includes exercises, real-world case studies, and examples of processes and documentation used in agentic Artificial Intelligence cyber investigation projects. Participants examine realistic investigative scenarios involving autonomous behavior, unauthorized access, suspicious tool usage, identity activity, evidence preservation, and incident reporting.
Assessment and Certification
Participants will be assessed through quizzes, assignments, case-based investigative activities, and a capstone project. Assessments evaluate the participant’s ability to identify evidence sources, analyze agent activity, reconstruct events, determine investigative findings, assess cybersecurity impact, and prepare professional investigation reports.
Upon successful completion of the program and required assessments, participants will receive the Certified Agentic Artificial Intelligence Cyber Investigator (CAAICI) certification.
Question Types
- Multiple Choice Questions
- Scenario-Based Questions
Passing Criteria
To pass the Certified Agentic Artificial Intelligence Cyber Investigator (CAAICI) Certification Program exam, candidates must achieve a score of 70% or higher.
Take the Next Step
Advance your capabilities in Artificial Intelligence security, cyber investigation, digital evidence analysis, and autonomous system incident response with the Certified Agentic Artificial Intelligence Cyber Investigator (CAAICI) Certification Program by Tonex. Build the professional expertise needed to investigate agent-driven cyber incidents, preserve defensible evidence, determine impact, and support secure and accountable Artificial Intelligence operations.