Develop the expertise to identify, exploit, and mitigate security vulnerabilities across AI systems and infrastructure.
As AI becomes increasingly integrated into products, operations, and decision making, new attack surfaces are emerging across models, prompts, data pipelines, agent workflows, APIs, and integrations. The Certified Offensive AI Security Professional (C|OASP) is a hands on, practitioner level credential focused on offensive AI security and validating the ability to ethically assess and attack AI systems.
- Why get trained: Learn to think like an attacker, uncover vulnerabilities across AI models and pipelines, test security controls, and apply offensive and defensive techniques to identify and reduce AI security risks.
- Why it matters: Traditional penetration testing may not fully address AI specific threats such as prompt injection, data poisoning, and model manipulation. Specialized AI security skills help organizations identify weaknesses and strengthen controls before deployment.
- Who should attend: Offensive Security Professionals, Threat Intelligence Professionals, Security Engineers, Defensive Security Professionals, AI/ML Engineers, and AI Security Architects.
Build practical offensive AI security capabilities and develop the skills to assess AI systems, validate security controls, and reduce operational risk. HRD Corp Claimable.
Overview
AI is transforming products, operations, and decision-making across industries. But when AI systems move into production, they open new attack paths, through models, prompts, data pipelines, agent workflows, APIs, and integrations, creating vulnerabilities adversaries are already targeting.
Traditional pentesting doesn’t fully cover LLM vulnerabilities. Prompt injection, data poisoning, and model manipulation require specialized offensive skills. Certified Offensive AI Security Professional is the first credential built specifically for AI red teamers.
C|OASP is a hands-on, practitioner-level credential that validates your ability to ethically attack AI systems so you can defend them with engineering-grade controls.
C|OASP is not about building AI models or running AI programs. It is about proving you can:
- Think like an attacker inside AI systems
- Uncover weaknesses across models and pipelines
- Validate security controls
- Reduce operational risk before deployment
This is the only credential built for offensive AI security work with outcomes you can
demonstrate.
Skills Covered
The C|OASP credential validates your ability to:
- Execute prompt injection, jailbreaking, and prompt chaining attacks
- Red-team AI agents, including memory corruption, tool misdirection, and checkpoint manipulation
- Apply OWASP LLM Top 10 and MITRE ATLAS frameworks
- Conduct adversarial ML attacks, including data poisoning and model extraction
- Build detection rules and hardening strategies for AI systems
Prerequisites
This course requires participants to have at least 3 Years of Cybersecurity Experience
Target Audience
C|OASP is designed for security professionals who wish to master offensive and defensive AI security techniques.
- Offensive Security
- Threat Intelligence
- Security Engineering
- Defensive Security
- AI/ML Engineering
- AI Security Architecture
Module 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.
Module 2: AI Reconnaissance and Attack Surface Mapping
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.
Module 3: AI Vulnerability Scanning and Fuzzing
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.
Module 4: Prompt Injection and LLM Application Attacks
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.
Module 5: Adversarial Machine Learning and Model Privacy Attacks
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.
Module 6: Data and Training Pipeline Attacks
Compromise AI systems through data poisoning and backdoor insertion targeting training pipelines and model integrity.
Module 7: Agentic AI and Model-to-Model Attacks
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.
Module 8: AI Infrastructure and Supply Chain Attacks
Explore offensive techniques targeting AI infrastructure, system integrations, and third-party dependencies, while learning how
to identify, exploit, and harden AI supply chain weaknesses.
Module 9: AI Security Testing, Evaluation, and Hardening
Apply structured AI security testing and evaluation methodologies to assess risk, validate controls, and implement hardening best practices across enterprise AI systems.
Module 10: AI Incident Response and Forensic
Master AI-specific incident response and forensics, concluding with hands-on engagement in AI red team activities.
Dates & Locations
February 8, 2027 - February 12, 2027
February 8, 2027 - February 12, 2027
May 24, 2027 - May 28, 2027
May 24, 2027 - May 28, 2027
August 23, 2027 - August 27, 2027
August 23, 2027 - August 27, 2027
November 22, 2027 - November 26, 2027
November 22, 2027 - November 26, 2027
Exam & Certification
Certified Offensive AI Security Professional (C|OASP)
The C|OASP certification validates a professional’s practical ability to identify, assess, and ethically exploit security vulnerabilities across modern AI systems, including AI models, LLM applications, data pipelines, agentic AI systems, APIs, infrastructure, and supply chains.
The certification focuses on hands-on offensive AI security, assessing the ability to apply specialized techniques such as AI reconnaissance, attack surface mapping, vulnerability scanning, fuzzing, prompt injection, adversarial machine learning, model privacy attacks, data poisoning, agentic AI attacks, and AI infrastructure and supply chain testing.
Through practical security testing and evaluation, candidates demonstrate their ability to think like an attacker, uncover weaknesses, validate security controls, and identify risks across the AI lifecycle. The certification also covers AI-specific incident response, forensic analysis, security hardening, and red team activities.
Achieving the Certified Offensive AI Security Professional (C|OASP) credential demonstrates practical expertise in offensive AI security and the ability to ethically assess AI systems, uncover vulnerabilities, and help organizations strengthen their AI security controls and reduce operational risk.
Training & Certification Guide
Frequently Asked Questions
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All courses are HRD Claimable.
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