Certified LLM/GenAI Security Officer (CCSO) Certification Program by Tonex
The CCSO Certification Program equips professionals with the knowledge and strategies to secure Large Language Models (LLMs) and Generative AI systems. As these technologies reshape industries, they also introduce new threat vectors that traditional security models cannot fully address. This program explores GenAI architecture, emerging threats, policy enforcement, and secure integration in enterprise environments. Participants will learn how to protect sensitive data, ensure model integrity, and assess risks associated with adversarial inputs, hallucinations, data poisoning, and misuse.
Cybersecurity is at the core of this training. As LLMs increasingly power applications in healthcare, finance, defense, and enterprise automation, security officers must address challenges like prompt injection, output manipulation, and model exfiltration. This course empowers security professionals to design policies, enforce governance, and manage GenAI deployment securely. With a strong focus on trust, compliance, and ethical use, CCSO certification enhances participants’ readiness to safeguard next-gen AI systems across critical sectors.
Audience:
- Cybersecurity Professionals
- AI and Machine Learning Engineers
- Risk and Compliance Officers
- Cloud Security Architects
- Chief Information Security Officers (CISOs)
- Enterprise Security Strategists
Learning Objectives:
- Understand LLM/GenAI architecture and threat surfaces
- Identify common GenAI vulnerabilities and attack types
- Apply secure design principles to GenAI applications
- Enforce AI governance, compliance, and audit controls
- Mitigate risks related to data privacy and output integrity
- Design and implement GenAI-specific security policies
Program Modules:
Module 1: LLM/GenAI Foundations and Ecosystem
- Overview of GenAI and LLM evolution
- Core architecture of transformer models
- Pre-training vs. fine-tuning risks
- Cloud-native GenAI deployment considerations
- Role of APIs and third-party integrations
- Impact of GenAI on enterprise cybersecurity
Module 2: Threat Landscape and Vulnerabilities
- Prompt injection and manipulation attacks
- Model inversion and extraction threats
- Data poisoning and training set attacks
- Hallucinations and misinformation risks
- Overreliance and automation bias issues
- Threat actors and adversarial use cases
Module 3: Secure Development and Deployment
- Secure LLM API configurations
- Protecting training and inference pipelines
- Controlling access to model inputs and outputs
- Security checks during model fine-tuning
- Isolation and sandboxing of GenAI systems
- Model monitoring for anomalous behavior
Module 4: Data Privacy and Governance
- Guardrails for PII and sensitive data
- Differential privacy techniques in GenAI
- Policy enforcement for user input filtering
- Logging and auditing for AI interactions
- Access control and encryption best practices
- Managing cross-border data concerns
Module 5: Compliance and Legal Considerations
- GenAI and regulatory frameworks (GDPR, HIPAA, etc.)
- Ethics in AI and model transparency
- Risk assessments for AI-based decisions
- Responsible use policies for enterprise models
- Third-party vendor and model vetting
- Security documentation and due diligence
Module 6: AI Security Strategy and Incident Response
- Developing an LLM security policy
- Red teaming and stress-testing LLMs
- Incident response for AI misuse and abuse
- Building cross-functional GenAI security teams
- Integrating LLM risk into SOC workflows
- Metrics for GenAI security effectiveness
Exam Domains:
- Fundamentals of LLM and GenAI Systems
- Threat Detection and AI-Specific Vulnerabilities
- Secure GenAI Development and Infrastructure
- Privacy, Ethics, and Governance in GenAI
- Regulatory Compliance for AI Deployments
- Strategic AI Security Planning and Response
Course Delivery:
The course is delivered through a combination of lectures, interactive discussions, and expert-led sessions facilitated by AI and cybersecurity professionals. Participants receive online resources, case studies, and templates for real-world application.
Assessment and Certification:
Participants are evaluated through quizzes, assignments, and a final capstone scenario. Upon successful completion, they will be awarded the Certified LLM/GenAI Security Officer (CCSO) certificate.
Question Types:
- Multiple Choice Questions (MCQs)
- True/False Statements
- Scenario-based Questions
- Fill in the Blank Questions
- Matching Questions (Matching concepts or terms with definitions)
- Short Answer Questions
Passing Criteria:
To pass the CCSO Certification Training exam, candidates must achieve a score of 70% or higher.
Join the frontline of GenAI security. Enroll in the CCSO program and gain critical skills to protect, govern, and guide the responsible use of powerful AI technologies. Prepare to lead in a world shaped by intelligent systems.