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Certified Offensive AI Security Professional (C|OASP)

 

The Certified Offensive AI Security Professional (C|OASP) is an advanced, hands-on EC-Council certification designed for cybersecurity professionals who want to master offensive security techniques for artificial intelligence systems, large language models (LLMs), and agentic AI. The program teaches learners how to identify, exploit, and mitigate AI-specific vulnerabilities through structured AI red teaming methodologies, covering prompt injection, LLM jailbreaking, adversarial machine learning, model extraction, data poisoning, AI supply chain attacks, agent manipulation, and AI incident response. Through practical labs aligned with the OWASP LLM Top 10, MITRE ATLAS, and industry best practices, participants gain the skills required to assess, secure, and defend modern AI applications and enterprise AI infrastructure against emerging real-world threats.

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Why Join this Program

  • Gain specialized expertise in offensive AI security and AI red teaming.
  • Learn how to identify, exploit, and mitigate vulnerabilities in AI systems, Large Language Models (LLMs), and AI agents.
  • Master advanced attack techniques such as prompt injection, LLM jailbreaking, adversarial machine learning, model extraction, and data poisoning.
  • Develop hands-on experience through realistic labs and AI attack simulations.
  • Learn industry-recognized frameworks, including the OWASP LLM Top 10 and MITRE ATLAS.
  • Build practical skills to assess the security of generative AI applications and AI-powered enterprise systems.
  • Understand AI governance, secure AI development, and responsible AI security practices.
  • Stay ahead of emerging AI cyber threats and evolving attack techniques.
  • Earn an industry-recognized EC-Council certification that validates your expertise in AI offensive security.
  • Enhance your career opportunities in AI security, penetration testing, red teaming, AI governance, and cybersecurity leadership.

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Program Overview

The Certified Offensive AI Security Professional (C|OASP) program is an advanced, hands-on cybersecurity training course designed to equip professionals with the knowledge and practical skills to assess, exploit, and secure artificial intelligence systems, Large Language Models (LLMs), generative AI applications, and AI agents. The curriculum covers the complete AI attack lifecycle, including AI threat modeling, prompt injection, LLM jailbreaking, adversarial machine learning, model extraction, data poisoning, AI supply chain attacks, agentic AI exploitation, and AI red teaming methodologies. Participants gain practical experience through immersive labs, real-world attack simulations, and offensive security exercises aligned with the OWASP LLM Top 10, MITRE ATLAS, and modern AI security frameworks. Upon completion, learners will be prepared to identify AI-specific vulnerabilities, perform comprehensive AI security assessments, and implement effective defensive strategies to protect enterprise AI environments from emerging cyber threats.

Key Features

  • Comprehensive AI Offensive Security Curriculum covering attacks against AI models, LLMs, and AI agents.
  • Hands-on AI Red Teaming Labs with realistic attack simulations and practical exploitation exercises.
  • OWASP LLM Top 10 & MITRE ATLAS Alignment to address the latest AI security threats and attack techniques.
  • Prompt Injection & LLM Jailbreaking techniques for assessing generative AI security.
  • Adversarial Machine Learning including evasion attacks, model manipulation, and adversarial examples.
  • AI Model Extraction & Data Poisoning to understand and mitigate model theft and training data attacks.
  • Agentic AI & AI Supply Chain Security covering vulnerabilities in AI agents, plugins, APIs, and third-party models.
  • Industry-Standard AI Security Tools for AI penetration testing, vulnerability assessment, and red teaming.
  • Real-World AI Attack Scenarios & Case Studies demonstrating emerging threats and defensive strategies.
  • Industry-Recognized EC-Council Certification validating expertise in offensive AI security and AI red teaming.
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Learning Path

  • Introduction to AI Security
    Understand artificial intelligence, machine learning, Large Language Models (LLMs), generative AI, and the evolving AI threat landscape.
  • AI Threat Modeling & Attack Surface Analysis
    Learn how to identify AI assets, map attack surfaces, and analyze risks across AI systems and applications.
  • Large Language Model (LLM) Security
    Explore LLM architectures, prompt engineering, prompt injection, jailbreak techniques, and model abuse scenarios.
  • AI Red Teaming Methodologies
    Apply structured offensive security frameworks to assess and simulate attacks against AI-powered systems.
  • Adversarial Machine Learning
    Perform adversarial attacks, model evasion, data poisoning, model extraction, and inference attacks.
  • Agentic AI & AI Supply Chain Security
    Assess AI agents, plugins, APIs, third-party models, and AI supply chain components for security weaknesses.
  • AI Penetration Testing Tools & Techniques
    Use specialized AI security tools to identify, validate, and exploit vulnerabilities in AI environments.
  • AI Governance, Defense & Mitigation
    Implement secure AI development practices, AI governance, model hardening, monitoring, and defensive controls.
  • Hands-on AI Labs & Real-World Attack Simulations
    Gain practical experience through immersive labs, AI red team exercises, and realistic attack scenarios.
  • Final Assessment & Certification Preparation
    Review core concepts, complete comprehensive AI security exercises, and prepare for the EC-Council C|OASP certification exam.

What Skills Will You Learn?

  • Perform offensive security assessments of AI systems, Large Language Models (LLMs), and generative AI applications.
  • Conduct AI red teaming exercises using industry-recognized methodologies and frameworks.
  • Identify and exploit prompt injection, prompt leaking, and LLM jailbreak vulnerabilities.
  • Perform adversarial machine learning attacks, including evasion, poisoning, and model manipulation.
  • Assess AI models for model extraction, membership inference, and model inversion attacks.
  • Evaluate AI agents, plugins, APIs, and AI supply chains for security weaknesses.
  • Apply the OWASP LLM Top 10 and MITRE ATLAS frameworks to identify and mitigate AI-specific threats.
  • Secure AI applications by implementing defensive controls, model hardening, and monitoring techniques.
  • Perform AI threat modeling, risk assessment, and vulnerability analysis across enterprise AI environments.
  • Use specialized AI security and penetration testing tools to validate AI system resilience.
  • Develop AI security reports with technical findings, risk ratings, and remediation recommendations.
  • Design and implement strategies to strengthen the security of AI-powered applications and enterprise AI ecosystems.
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Jobs You Can Land with this Certification:

  • Offensive AI Security Professional
  • AI Security Engineer
  • AI Red Team Operator
  • AI Penetration Tester
  • AI Application Security Engineer
  • Generative AI Security Specialist
  • Large Language Model (LLM) Security Engineer
  • AI Threat Researcher
  • AI Vulnerability Assessment Consultant
  • AI Security Consultant
  • Offensive Security Engineer
  • Red Team Specialist
  • Cybersecurity Researcher (AI Security)
  • Application Security (AppSec) Engineer
  • AI Governance & Risk Analyst
  • Machine Learning Security Engineer
  • AI Incident Response Analyst
  • AI Security Architect
  • AI Security Operations (AI SecOps) Engineer
  • Chief AI Security Officer (CAISO) (with appropriate experience)
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Exam Details

Exam Attribute Details
Certification EC-Council Certified Offensive AI Security Professional (C|OASP)
Exam Code 312-52
Exam Format 65 Multiple Choice Questions (MCQs) + 5 Performance-Based Practical Challenges
Total Questions 70 Questions
Exam Duration 6 Hours
Passing Score 70–80% (Varies by exam form)
Exam Availability EC-Council ECC Exam Portal
Delivery Mode Live Online Proctored Examination
Assessment Areas AI reconnaissance, prompt injection, LLM jailbreaking, adversarial machine learning, model extraction, data poisoning, agentic AI attacks, AI supply chain security, AI red teaming, AI incident response, and AI system hardening.
Recommended Experience Recommended for cybersecurity professionals with knowledge of penetration testing, AI/ML fundamentals, and application security.
Certification Awarded By EC-Council
Exam Syllabus

Exam Preparation

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