Module 1: TrendAI Vision One ™ Cloud Security Fundamentals
Introduction to TrendAI Vision One ™Architecture
This module introduces the core architecture of TrendAI Vision One™, focusing on its role in securing multi-cloud environments.
Students will learn how the platform integrates with AWS, Azure, and GCP, providing unified visibility and centralized control. The session explains key components such as connectors, dashboards, and policy engines, ensuring participants understand how these elements work together to deliver comprehensive security.
By the end of this module, learners will appreciate the strategic importance of TrendAI Vision One™ in reducing complexity and improving operational efficiency in cloud security management.
Understanding Cloud Threat Landscape
This topic explores the evolving nature of cloudbased threats, including misconfigurations, identity compromises, and container vulnerabilities. Students will analyze real-world attack scenarios to understand how adversaries exploit weaknesses in cloud environments. The module emphasizes why traditional security approaches fail in dynamic cloud ecosystems and how TrendAI Vision One™ addresses these gaps. Participants will gain insights into risk prioritization and proactive defense strategies, setting the stage for advanced security implementations later in the course.
Module 2: Container Security
Container Security Overview and Best Practices
This module dives into the fundamentals of container security, explaining why containers introduce unique risks compared to traditional workloads. Students will learn about common vulnerabilities in container images, runtime threats, and compliance challenges. The session covers best practices for securing containerized applications, including image scanning, policy enforcement, and runtime monitoring. By mastering these concepts, participants will be prepared to implement robustsecurity measures for Kubernetes and other container orchestration platforms.
Implementing Container Security in TrendAI Vision One
Building on the previous module, this topic provides hands-on experience in deploying and configuring container security features within TrendAI Vision One™. Students will practice integrating container registries, setting up artifact scanning, and applying runtime protection policies. The module also covers how to interpret security events and respond to incidents effectively.
By the end of this session, learners will have the skills to secure containerized workloads throughout the CI/CD pipeline.
Category 3: File Storage Security
Securing Cloud -Based File Repositories
This module focuses on protecting data stored in cloud file systems such as AWS S3, Azure Blob Storage, and Google Cloud Storage. Students will learn how TrendAI Vision One™ scans files for malware, enforces access controls, and prevents data leakage. The session includes practical exercises on configuring file security policies and analyzing detection logs. Participants will also explore compliance considerations for sensitive data stored in cloud environments, ensuring they can maintain regulatory alignment while safeguarding critical assets.
Category 4: Cloud Posture Management
Compliance and Risk Assessment in Multi -Cloud Environments This topic introduces the concept of cloud posture management and its role in maintaining security and compliance. Students will learn how TrendAI Vision One™ evaluates cloud configurations against industry benchmarks such as CIS and NIST. The module covers generating posture reports, interpreting risk scores, and applying remediation strategies. By mastering these skills, participants will be able to proactively manage compliance and reduce the likelihood of breaches caused by misconfigurations.
Category 5: Advanced Capabilities – CREM andXDR
Cyber Risk Exposure Management (CREM )
This module provides an in-depth look at CREM within TrendAI Vision One™, explaining how it identifies and prioritizes risks across the entire cloud attack surface. Students will learn to use CREM dashboards to visualize vulnerabilities, assign risk scores, and plan remediation efforts. The session emphasizes how CREM supports strategic decision-making by focusing resources on the most critical threats. Practical exercises will reinforce the ability to operationalize CREM for continuous risk reduction.
Extended Detection and Response (XDR) for Cloud Workloads
The final module explores how XDR enhances threat detection and incident response in cloud environments. Students will learn to correlate telemetry from endpoints, servers, and cloud workloads, enabling faster and more accurate threat identification. The session covers automated response workflows, playbook creation, and integration with SOC operations.
By the end of this module, participants will be equipped to leverage XDR for comprehensive, enterprise-grade cloud security.