Agent Threat Modeling Training by Tonex
Agent Threat Modeling Training by Tonex equips professionals with structured methods for identifying, analyzing, and mitigating security threats involving autonomous Artificial Intelligence (AI) agents. Participants explore agent architectures, operational boundaries, delegated authority, tool interactions, trust relationships, and emerging attack techniques.
Autonomous agents introduce new cybersecurity challenges through independent decision-making, interconnected workflows, and access to sensitive resources. Effective agent threat modeling strengthens cybersecurity resilience by identifying unauthorized actions, prompt injection, data exposure, and privilege misuse. Integrating threat modeling into cybersecurity programs improves defensive design, accountability, and operational oversight.
The course uses a practical training approach that includes exercises, real-world case studies, and examples of processes and documentation used in agent threat modeling and cybersecurity projects.
Learning Objectives
Upon completion of this course, participants will be able to:
- Explain fundamental agent threat modeling concepts, methodologies, and security objectives.
- Identify security boundaries, assets, dependencies, and trust relationships within autonomous agent architectures.
- Analyze attack surfaces associated with agent reasoning, tool access, delegated permissions, and external interactions.
- Recognize prompt injection, malicious instructions, unauthorized delegation, and agent manipulation techniques.
- Develop structured threat scenarios, attack paths, and misuse cases involving autonomous agents.
- Evaluate security risks using likelihood, impact, exposure, and operational consequences.
- Apply protective controls to strengthen agent authorization, monitoring, and human oversight.
- Improve cybersecurity resilience through systematic agent threat identification, mitigation planning, and continuous security evaluation.
- Document threat modeling findings, security requirements, residual risks, and governance decisions.
Audience
This course is designed for:
- Cybersecurity Professionals
- Artificial Intelligence Security Professionals
- Security Architects and Engineers
- Agentic Artificial Intelligence Developers
- Threat Modeling Specialists
- Application Security Professionals
- Security Operations Professionals
- Risk Management Professionals
- Information Security Managers
- Artificial Intelligence Governance Professionals
- Cloud Security Engineers
- Enterprise Security Architects
- Security Assessment Professionals
- Technology Risk and Compliance Professionals
Course Modules
Module 1: Agent Threat Modeling Fundamentals
- Agentic Artificial Intelligence architecture and security fundamentals
- Autonomous agent capabilities, goals, and decision boundaries
- Threat modeling principles for agent-based applications
- Agent assets, identities, permissions, and dependencies
- Trust boundaries across agent execution environments
- Security responsibilities throughout the agent development lifecycle
Module 2: Agent Attack Surface Identification
- Entry points across agent interfaces and workflows
- Prompt injection and malicious instruction pathways
- Tool access vulnerabilities and unauthorized operations
- Agent memory, context, and knowledge manipulation
- External information sources and untrusted content
- Multi-agent communication and trust relationship weaknesses
Module 3: Agent Threat Scenarios and Attack Paths
- Unauthorized agent actions and privilege escalation
- Agent goal manipulation and workflow hijacking
- Sensitive information disclosure and data exfiltration
- Credential misuse and delegated authority abuse
- Malicious tool responses and indirect instruction attacks
- Compromised agents and cascading security failures
Module 4: Agent Security Risk Assessment
- Threat likelihood, severity, and business impact evaluation
- Attack feasibility and exploitability assessment techniques
- Risk prioritization across agent workflows and permissions
- Security exposure from third-party agent integrations
- Evaluating operational consequences of autonomous decisions
- Risk registers, mitigation priorities, and acceptance criteria
Module 5: Agent Security Controls and Mitigation
- Least privilege and agent authorization enforcement
- Secure tool invocation and permission validation
- Input validation and untrusted instruction handling
- Agent activity monitoring and behavioral anomaly detection
- Human approval requirements for sensitive operations
- Containment, escalation, and recovery control strategies
Module 6: Threat Modeling Governance and Documentation
- Integrating agent threat modeling into security governance
- Threat modeling documentation and security assessment reports
- Agent security requirements and control mapping procedures
- Security review processes and stakeholder accountability
- Continuous threat evaluation and emerging risk monitoring
- Maintaining threat registers and remediation tracking records
Strengthen autonomous agent security and develop practical expertise in identifying emerging Artificial Intelligence threats. Enroll in Agent Threat Modeling Training by Tonex to advance threat analysis, risk assessment, defensive security design, and cybersecurity governance capabilities.