Certified Offensive AI Security Professional (C|OASP)

LLMs are vulnerable. Prompt injection can bypass guardrails. Data poisoning can corrupt models. EC-Council’s Certified Offensive AI Security Professional (C|OASP) credential validates that you can red-team AI systems, exploit vulnerabilities in LLMs and agents, and build defenses that survive real-world attacks.

Course Curriculum

Module 01: Offensive AI and AI System Hacking Methodology

AI & machine learning fundamentals from an offensive security perspective
AI attack surfaces and threat landscapes
MITRE ATLAS adversary techniques
AI system hacking methodologies
AI attack taxonomies and models
Offensive AI scoping fundamentals
OWASP LLM & ML Top 10 (2025) mapping

Module 02: AI Reconnaissance and Attack Surface Mapping

AI-focused OSINT techniques
Identifying and profiling AI assets
Intelligence gathering from AI data sources
Attack surface discovery and mapping
AI endpoint and API enumeration
Model and vector store analysis
Exposure mitigation and hardening controls
AI threat intelligence for continuous monitoring

Module 03: AI Vulnerability Scanning and Fuzzing

AI vulnerability assessment principles
Threat discovery techniques
Scanning AI models and pipelines
AI deployment vulnerability analysis
AI-specific fuzzing methods
Integration into AI security workflows

Module 04: Prompt Injection and LLM Application Attacks

LLM architecture and trust boundaries
Prompt injection attacks
Jailbreaking techniques
System prompt leakage
Sensitive information disclosure risks
Output manipulation and misinformation attacks
Advanced prompt exploitation strategies
Secure LLM application design

Module 05: Adversarial Machine Learning and Model Privacy Attacks

Adversarial ML attack classes
Adversarial input attacks across data modalities
Privacy and inference attacks
Model extraction techniques
Robustness and trustworthiness evaluation
Defensive strategies for model privacy

Module 06: Data and Training Pipeline Attacks

AI training pipeline architecture
Data poisoning attacks
Backdoor insertion techniques
Trojan attacks during model training
Securing data and training pipelines

Module 07: Agentic AI and Model-to-Model Attacks

Agentic AI architecture and attack surfaces
Excessive agency exploitation
Cross-LLM attack vectors
Model-to-model attacks
Denial-of-wallet attacks
Workflow and orchestration layer attacks
Defensive strategies for agentic AI

Module 08: AI Infrastructure and Supply Chain Attacks

AI infrastructure components
System integration architectures
AI deployment pipeline vulnerabilities
Abuse of tools, plugins, and APIs
AI supply-chain threat assessment
Dependency risk analysis
Infrastructure and supply-chain hardening

Module 09: AI Security Testing, Evaluation, and Hardening

AI security testing methodologies
AI evaluation techniques
Red-team frameworks for AI
Vulnerability validation and reporting
AI risk assessment
Security hardening best practices

Module 10: AI Incident Response and Forensics

AI-specific incident detection
AI incident response procedures
AI log and telemetry analysis
Digital evidence collection
Post-incident root cause analysis
Hands-on AI red team activities

What You'll Learn

Perform AI red teaming and offensive security assessments against LLMs and AI systems.
Identify and exploit vulnerabilities such as prompt injection, jailbreaking, data poisoning, and model extraction.
Assess AI attack surfaces across models, agents, APIs, and training pipelines.
Apply industry frameworks including OWASP LLM Top 10 and MITRE ATLAS.
Implement security controls and hardening strategies to defend AI applications.

Prerequisites

Basic understanding of cybersecurity and penetration testing concepts.
Familiarity with web applications, APIs, and modern attack methodologies.
Knowledge of networking, security operations, or security assessment practices.
Recommended: 3+ years of cybersecurity experience.

Exam Details

Duration

6 hours

Passing Score

70–80%

Format

Multiple Choice Questions (MCQs) and Performance-Based Questions

Delivery Method

Online via the EC-Council Exam Portal

Who Should Take This Course

Penetration Testers, Ethical Hackers, and Red Team Professionals

Security Engineers, SOC Analysts, and Incident Responders

AI/ML Engineers, GenAI Developers, and MLOps Professionals

Application Security and Product Security Engineers

AI Security Architects and Risk Assessment Professionals

Anyone looking to specialize in AI Red Teaming and Offensive AI Security practices.

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