CERTIFIED OFFENSIVE AI SECURITY PROFESSIONAL

10 Weeks

Duration

Online

Mode of Study

Certified Offensive AI Security Professional
(C|OASP)

Certification

$465

Cost Per Credit Hour

Enroll Now |
Download Brochure

Course Overview

It’s clear that Artificial Intelligence (AI) is a generational technology that will upend established business practices across every industrial sector. But as AI becomes increasingly embedded into workflows, it presents new cyberattack vectors through language models, prompts, data pipelines, agentic functions, APIs, and other integrations. Traditional cybersecurity measures don’t adequately cover AI-based vulnerabilities.
This state-of-the-art course teaches you specialized offensive skills needed to defend AI systems from prompt injection, data poisoning, LLM manipulation, and other emerging threats. Your career prospects and earning potential will be enhanced by earning the first credential built specifically for AI red teamers – C|OASP.

Admission Inquiry

Highlights of This Course

Cutting-Edge Courseware

10 modules featuring immersive video lectures and digital books for an in-depth understanding of every topic.

Virtual Labs

Simulate real-world scenarios for hands-on practice with the latest cybersecurity tools.

Quizzes

Engaging quizzes after each module that measure and reinforce your knowledge of the topics covered.

Discussions

Interactive discussion boards where you exchange ideas and views on the course topics with your peers and professors.

Essential Tools

Software tools that enhance your learning experience, such as Grammarly.

24x7 Online Library

Round-the-clock online library with an expansive collection of free-to-use learning resources.

Cybersecurity Certification

Includes EC-Council's industry-approved Certified Offensive AI Security Professional (C|OASP) certification.

Inquire Now |

Why Pursue a Career in AI Cybersecurity?

The global AI cybersecurity market is predicted to grow from $35.40 billion in 2026 to approximately $167.77 billion by 2035. (Source:Precedence Research)

The number of cybersecurity jobs that explicitly require AI security skills grew by approximately 62% from 2024 to 2025. (Source: National Information Technology Innovation Center)
The annual pay for an AI Security Engineer in the U.S. ranges from $144,000 to $227,000, with a median salary of $180,000. (Source:Glassdoor)

Earning Potential

Weekly Modules

Week-1Module 1 – Offensive AI and AI System Hacking Methodology

Build a foundation in offensive AI security by learning how AI systems are designed, where they fail, and how adversaries exploit them, using structured hacking methodologies and globally recognized AI security frameworks.

Learn advanced AI-focused OSINT techniques to identify, enumerate, and analyze AI assets, data pipelines, models, APIs, and attack surfaces, and apply exposure mitigation and hardening strategies to support continuous AI security monitoring.

Master AI-specific vulnerability assessment and fuzzing techniques to identify, analyze, and mitigate security weaknesses across modern AI systems and applications.

Analyze and exploit LLM trust boundaries using advanced prompt injection, jailbreaking, and output manipulation techniques, while identifying risks related to sensitive data exposure and insecure LLM application design.

Execute and analyze adversarial machine learning, privacy, and model extraction attacks to assess AI system robustness, trustworthiness, and risk, and apply defensive strategies to mitigate them.

Compromise AI systems through data poisoning and backdoor insertion targeting training pipelines and model integrity.

Analyze and exploit autonomous AI agents and multi-model architectures by targeting excessive agency, cross-LLM interactions, orchestration workflows, and unbounded resource consumption, while understanding defensive strategies to secure agentic systems.

Explore offensive techniques targeting AI infrastructure, system integrations, and third-party dependencies, while learning how to identify, exploit, and harden AI supply chain weaknesses.

Apply structured AI security testing and evaluation methodologies to assess risk, validate controls, and implement hardening best practices across enterprise AI systems.

Master AI-specific incident response and forensics, concluding with hands-on engagement in AI red team activities.

What You Will Learn

  • Understand AI and machine learning fundamentals from an offensive security perspective
  • Identify AI attack surfaces, threat landscapes, and adversary techniques aligned to MITRE ATLAS
  • Apply AI system hacking methodologies, frameworks, and risk implications
  • Classify AI attack taxonomies and models
  • Apply OSINT tools and techniques to identify and profile AI assets
  • Gather intelligence from AI data sources and training pipelines
  • Discover and map AI attack surfaces using publicly available intelligence
  • Enumerate AI endpoints, services, APIs, and exposed parameters
  • Identify and analyze AI models and vector stores from an attacker’s perspective
  • Understand core principles of AI vulnerability assessment and threat discovery
  • Use tools and techniques for scanning vulnerabilities in AI models, pipelines, and deployments
  • Apply practical fuzzing methods tailored for AI systems and model interfaces
  • Integrate scanning and fuzzing into AI security workflows for proactive risk mitigation
  • Execute prompt injection and jailbreaking techniques in real-world LLM applications
  • Identify sensitive information disclosure and system prompt leakage risks
  • Execute practical adversarial input attacks across data modalities
  • Apply privacy, inference, and model extraction attack techniques
  • Understand AI data and training pipeline architecture and threat surfaces
  • Execute practical data poisoning techniques and attack scenarios
  • Understand agentic AI architecture and attack surface
  • Identify cross-LLM and model-to-model attack vectors
  • Assess denial-of-wallet risks and unbounded resource consumption
  • Understand AI security testing methodologies and evaluation techniques
  • Apply red team frameworks for offensive AI assessment
  • Detect and respond to AI-specific security incidents
  • Collect and analyze AI logs, telemetry, and digital evidence
And much more!

Skills You Will Gain

Jobs You Can Prepare For

AI Security Engineer

AI Red Team Specialist

Offensive Security Engineer (AI/LLM)

Adversarial AI Security Analyst

AI Threat Hunter

AI Incident Response Engineer

AI Forensics Analyst

MLOps/AIOps Security Specialist

LLM Systems Engineer

AI Model Risk/AI Risk & Assurance Specialist

AI Product Security Manager

AI Security Program Manager

Cyber Threat Intelligence Analyst (AI Focus)

AI Risk Advisor

And Many More!

Total Course Fee

$1,395

Inquire now|
  • Cost Per Credit Hour: $465
  • Technology Fee Per Term: $50
  • Transcript Fee: $10 (plus shipping, if international)

Admission Criteria

  • You must be aged 18 years or older.
  • You must have at least 3 years of cybersecurity work experience
  • You must have a high school diploma (or equivalent), college degree, or relevant certification.

How to Apply

Step 01 :

Fill out the NDS application form and submit it to our Enrollment Advisor.

Step 02 :

Send us scanned copies of your official government identification and documents proving your education.

Step 03 :

Pay the one-time $100 application fee.

Voices of Success: Hear from Our Alumni

Here’s what our students say about this course and how it helped advance their cybersecurity careers.

Inquire Now |

Frequently Asked Questions

What is the Certified Offensive AI Security Professional (C|OASP) certification?

It’s a certification designed for cybersecurity professionals who must think like attackers and defend AI like engineers. It trains you to red-team LLMs, exploit AI systems, and defend enterprise AI before cybercriminals can breach AI systems.

C|OASP is ideal for red-team and blue-team cybersecurity professionals, SOC analysts, penetration testers, AI/ML engineers, DevSecOps specialists, and other individuals who ensure AI safety, particularly in sectors like finance, healthcare, national security, and tech.

Yes. As this is an advanced-level course, you will need at least 3 years of prior cybersecurity experience to be eligible for enrollment.

Admission Inquiry

Admission Inquiry