Offensive Security AI Security (OSAI)

The Offensive Security AI Security (OSAI) course is an advanced hands-on cybersecurity training program designed to equip security professionals with the knowledge and practical skills required to assess, exploit, and secure modern Artificial Intelligence (AI) and Large Language Model (LLM) applications. As organizations increasingly adopt AI-powered technologies, new attack surfaces and security challenges have emerged, creating a critical need for professionals who understand both offensive security and AI systems.

This course provides a comprehensive understanding of AI architectures, machine learning models, LLM ecosystems, and the security risks associated with AI deployments. Participants will learn how adversaries target AI systems through techniques such as prompt injection, jailbreak attacks, indirect prompt manipulation, model extraction, data poisoning, adversarial machine learning, sensitive information disclosure, and AI supply chain attacks.

Through realistic labs and practical exercises, students will perform security assessments against AI-powered applications, identify vulnerabilities in LLM integrations, evaluate AI model security, and understand how attackers exploit weaknesses in AI infrastructures. The course also covers industry-recognized AI security frameworks, threat modeling methodologies, secure AI development practices, and defensive strategies to mitigate emerging AI threats.

By the end of the course, participants will be capable of conducting professional AI security assessments, identifying vulnerabilities in AI-driven environments, and implementing security controls to protect AI systems against sophisticated attacks.

Key Learning Outcomes

• Understand the fundamentals of AI, Machine Learning, and Large Language Models (LLMs).
• Identify common attack vectors targeting AI applications and LLMs.
• Perform prompt injection and jailbreak testing against AI systems.
• Assess AI model security and evaluate model-related vulnerabilities.
• Analyze risks associated with AI plugins, agents, and third-party integrations.
• Understand adversarial machine learning and model manipulation techniques.
• Conduct AI threat modeling and security risk assessments.
• Secure AI applications using industry best practices and security frameworks.
• Evaluate AI supply chain and infrastructure security risks.
• Generate professional AI security assessment reports.

Target Audience

Prerequisites

• Networking Fundamentals
• Web Application Security
• Linux Operating System
• Penetration Testing Concepts
• Basic Python Programming (Recommended)

Hands-On Labs

• AI Application Security Testing
• LLM Vulnerability Assessment
• Prompt Injection Exploitation
• AI Agent Security Testing
• Model Extraction Scenarios
• Data Poisoning Demonstrations
• AI Threat Modeling Exercises
• AI Security Reporting and Remediation

Certification Outcome

Upon successful completion, participants will possess the practical skills required to assess, exploit, and secure AI-driven applications and will be prepared to address the rapidly evolving challenges of AI security in modern enterprise environments.