Certified Offensive AI Security Professional
Master the Tactical Methodology to Hack LLMs and Secure Agentic AI, the Global Command for Offensive Teams
LLMs are vulnerable. Prompt injection bypasses guardrails. Data poisoning corrupts models. This credential validates you can red-team AI systems, exploit vulnerabilities in LLMs and agents, and build defenses that survive real-world attacks.
Attack Vectors
Prompt injection. Data poisoning. Model theft. Attackers are exploiting AI faster than security teams can learn to defend.
Your Credential
Certified Offensive AI Security Professional. Validate you can simulate attacks, find vulnerabilities, and harden AI systems.
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AI Red-Teaming Is a New Discipline
Traditional pentesting doesn’t cover LLM vulnerabilities. Prompt injection, data poisoning, and model manipulation require specialized offensive skills. C|OASP is the first credential built specifically for AI red teamers.
The Problem
- Prompt injection impacts 73%+ of production AI deployment#
- No standardized AI red-teaming methodology
- Security teams lack LLM exploitation skills
C|OASP CREDENTIAL VALIDATES
The C|OASP certification equips you to red-team AI systems end-to-end, from prompt injection to model exploitation. Master offensive techniques that break AI before attackers do.
- Master prompt injection, jailbreaking, and guardrail bypass
- Learn OWASP LLM Top 10 & MITRE ATLAS attack chains
- Build AI defenses that survive adversarial testing
Source: * IBM X-Force Threat Intelligence, 2024; ** Palo Alto Networks; # Resecurity, citing OWASP Top 10 for LLM Applications (2025)
Source: * IBM X-Force Threat Intelligence, 2024; ** Palo Alto Networks; # Resecurity, citing OWASP Top 10 for LLM Applications (2025)
Red-team agentic AI systems
Build defenses that survive real attacks
"Prompt injection bypasses every guardrail you've built."
Hack LLMs. Break Agents. Secure AI.
VALIDATE YOUR
LLM EXPLOITATION SKILLS
Over 73% of LLMs are vulnerable to prompt injection.
Traditional pentesting doesn’t cover AI-specific attack vectors. COASP trains you to exploit LLMs, agents, and AI pipelines, then build defenses that actually work.
The Market Problem
- Pentesters don't know how to exploit LLMs or AI agents
- No standardized methodology for AI red-teaming
- Traditional vulnerability scanners miss AI-specific flaws
- SOC teams can't detect AI-powered attacks
- Security architects don't understand AI threat models
Skills This Program Verifies
The COASP credential validates your ability to:
- Execute prompt injection, jailbreaking, and prompt chaining attacks
- Red-team AI agents: memory corruption, tool misdirection, and checkpoint manipulation
- Apply OWASP LLM Top 10 and MITRE ATLAS frameworks
- Conduct adversarial ML attacks: data poisoning, model extraction
- Build detection rules and hardening strategies for AI systems
Organizations need professionals with verified offensive AI skills. This credential proves you have them.
20+
Target Roles
Who is C|OASP Ideal For
C|OASP is designed for security professionals who want to master offensive and defensive AI security techniques.
Offensive Security
Defensive Security
Threat Intelligence
AI/ML Engineering
Security Engineering
AI Security Architecture
The market does not need more AI tools. It needs AI security professionals.
Be the professional who exposes weaknesses in AI systems before attackers do and helps organizations deploy AI securely at scale.
Program Overview
10 comprehensive modules!
Master offensive AI security from reconnaissance to red teaming. The C|OASP certification covers attack methodologies, vulnerability exploitation, and incident response.
Offensive AI and AI System Hacking Methodology
Build a strong foundation in offensive AI security by understanding how AI systems work, where they fail, and how they are attacked, using structured hacking methodologies and globally recognized AI security frameworks.
WHAT YOU WILL LEARN
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.
WHAT YOU WILL LEARN
AI Vulnerability Scanning and Fuzzing
Master AI-specific vulnerability assessment and fuzzing techniques to identify, analyze, and mitigate security weaknesses across modern AI systems and applications.
WHAT YOU WILL LEARN
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.
WHAT YOU WILL LEARN
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.
WHAT YOU WILL LEARN
Data and Training Pipeline Attacks
Compromise AI systems through data poisoning and backdoor insertion targeting training pipelines and model integrity.
WHAT YOU WILL LEARN
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 for securing agentic systems.
WHAT YOU WILL LEARN
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.
WHAT YOU WILL LEARN
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.
WHAT YOU WILL LEARN
AI Incident Response and Forensics
Master AI-specific incident response and forensics, concluding with hands-on engagement in AI red team activities.
WHAT YOU WILL LEARN
Offensive AI
Security
Methodology
From reconnaissance to exploitation, testing to hardening, there is a systematic approach to securing AI systems against adversarial threats.
This framework equips you to think like an attacker and defend like an expert.
01 RECON
Map AI system architectures, enumerate exposed endpoints, and build threat models. Profile training pipelines, data flows, and inference APIs to identify where defenses are weakest.
02 EXPLOIT
Execute prompt injection, jailbreaking, data poisoning, and model extraction attacks to validate AI system weaknesses and document exploitable gaps
03 DEFEND
Implement guardrails, detection mechanisms, and incident response procedures to harden AI systems and ensure resilient, secure deployments
C|OASP
Framework
The Threat Landscape
WHY TRADITIONAL
SECURITY
FAILS AGAINST AI
AI systems introduce novel attack vectors that traditional security tools and methodologies cannot detect or prevent. Understanding these threats is the first step to defending against them.
Prompt Injection
Attackers manipulate LLM inputs to bypass safety guardrails and extract sensitive data or execute unauthorized actions.
Model Extraction
Data Poisoning
Jailbreaking
Hands-On AI Offensive Security Techniques
RED-TEAM.
EXPLOIT.
DEFEND.
Master the offensive techniques that break AI systems before attackers do. From prompt injection to model extraction, learn to think like an adversary and defend like an engineer.
Multi-Protocol Reconnaissance
Enumerate AI-related endpoints across REST and gRPC services
Telemetry Analysis to Map AI Decision Boundaries
Analyze model outputs to reverse-engineer decision logic and thresholds
API Reconnaissance
Discover and map AI API endpoints, parameters, and authentication mechanisms
AI Reconnaissance via Model Fingerprinting
Identify AI models, versions, and configurations through behavioral analysis
Transfer, Boundary & Noise Attacks
Perform black-box adversarial attacks across AI model architectures
PGD Attacks on Audio Models
Deploy gradient attacks on audio classification and transcription models
Cross-LLM Attacks
Assess and exploit attack vectors in cross-LLM systems
API Reconnaissance & Model Extraction
Discover AI API endpoints and extract model weights from exposed infrastructure
RAG Poisoning Attacks
Inject malicious content into retrieval-augmented generation pipelines
PGD Attacks on Image Classifiers
Execute gradient-based adversarial attacks on computer vision models
FGSM & PGD Attacks on Image Classifiers
Execute gradient-based adversarial attacks on computer vision models
Atheris
AFL
CleverHans
ART
Foolbox
Alibi Detect
TFDV
Fairlearn
IBM AI Fairness 360
PyRIT
Burp Suite
OWASP ZAP
Prompt Fuzzer
ToolFuzz
Tensorfuzz
FuzzyAI
FuzzyAI
AI SECURITY EXPERTS EVERYWHERE
Every sector needs AI security experts!
With 87% of organizations facing AI-driven attacks, offensive security skills are mission-critical. C|OASP certifies you to red-team AI systems and defend against adversarial threats across every sector.
$28.6B¹
GLOBAL AI-ENHANCED BREACH LOSSES
Finance & Banking
AI fraud model hardening, LLM chatbot security, regulatory compliance testing
38.9%²
TECH EMPLOYEE AI ADOPTION
Technology
Enterprise LLM security, RAG pipeline hardening, AI DevSecOps integration
HIPAA
COMPLIANCE CRITICAL
Healthcare
Medical AI red-teaming, HIPAA-compliant security testing, clinical AI validation
DCWF
ALIGNED CURRICULUM
Government
DoD AI security frameworks, critical infrastructure protection, counter-adversarial ML
85%³
CONSIDER ADVERSARIAL AI A TOP SECURITY PRIORITY
Defense
Aerospace security, military systems, supply chain protection
Sources: ¹Market.Biz; ²Cyberhaven 2025; ³Gitnux
Threat Analysis
AI Security Monitoring
Network Defense
Infrastructure Protection
Red Team Ops
Offensive Security Testing
Prepares You For
The C|OASP certification opens doors to cutting-edge roles in offensive AI security, adversarial research, and AI risk management.
Offensive AI Security
- AI Red Team Specialist/Adversarial AI Engineer
- Offensive Security Engineer (AI/LLM Focus)
- Adversarial AI Security Analyst
AI Research & Analysis
- Adversarial Machine Learning Researcher
- AI Threat Hunter/AI Security Analyst
- AI Malware & Exploit Analyst
AI Incident & Testing
- AI Incident Response Engineer
- AI Test & Evaluation Specialist
- Cyber Threat Intelligence (CTI) Analyst – AI Focus
AI Engineering & Ops
- Secure AI Engineer/AI Security Architect
- ML Ops/AI Ops Security Specialist
- LLM Systems Engineer
AI Risk & Assurance
- AI Model Risk Specialist
- AI Risk & Assurance Specialist
- AI Risk Advisor/Consultant
AI Security Leadership
- Security Program Manager (AI Security)
- AI Product Security Manager
THE AI SECURITY GAP
ORGANIZATIONS
CAN'T SECURE
AI SYSTEMS
AI attacks are evolving faster than defenses, and most organizations lack offensive security expertise to test their AI systems.
Enterprises need certified AI security professionals who can red team LLMs, exploit vulnerabilities, and harden AI systems before attackers strike.
87% of organizations faced AI driven attacks in 2024.¹ OWASP warns that LLMs have 10 critical vulnerability categories most teams do not test.²
Sources: ¹ IBM X-Force Threat Intelligence, 2024; ² OWASP LLM Top 10, 2024
The Security Gap Organizations Face
- Companies deploy AI but cannot identify adversarial vulnerabilities
- Security teams understand networks but not AI-specific attack vectors
- ML engineers build models but do not red-team their own systems
- Result: AI deployments without security testing = breach waiting to happen
What This Credential Validates
Verify the skills that make you the AI leader organizations need:
- This credential validates your ability to red-team AI systems
- Verified skills in prompt injection, jailbreaking, and model exploitation
- Credential proves confidence testing enterprise AI defenses
- Industry-recognized proof of offensive AI security expertise
- Validation that you can find vulnerabilities before attackers do
What Your Organization Gets
Solve the AI security crisis:
- Identify AI vulnerabilities before production deployment
- Build robust defenses against adversarial AI attacks
- Protect LLMs and AI agents from exploitation
- Clear security validation for AI investments
OFFENSIVE AI SECURITY SALARY DATA
What AI Security Professionals Are Earning in 2026
Demand for professionals who can simulate adversarial attacks, test AI systems, and defend enterprise AI continues to outpace supply.
$175K
Average Salary (US)
28K+
Open Positions
AI Security Engineer
$183,000
Median salary
Range: $140,000 – $210,000
Source: Glassdoor.com
AI Engineer
$140,000
Median salary
Range: $112,000 – $178,000
Source: Glassdoor.com
AI Data Engineer
$112,000
Median salary
Range:$99,000 – $136,000
Source: 6figr.com
Senior Machine Learning Engineer
$164,000
Median salary
Range: $121,000 – $207,000
Source: Payscale.com
Organizations will pay premium salaries for professionals who can solve the AI security crisis. C|OASP makes you that solution.
AI Security Salary Data
What AI Security Pros Are Earning in 2026
Demand for professionals who can simulate adversarial attacks, test AI systems, and defend enterprise AI continues to outpace supply.
Adversarial AI Security Analyst
$188,000
Median salary
Range: $146,000 – $230,000
Adversarial Machine Learning Researcher
$173,000
Median salary
Range: $125,000 – $221,000
AI Threat Hunter / AI Security Analyst
$133,500
Median salary
Range: $113,600 – $153,500
AI Incident Response Engineer
$138,500
Median salary
Range: $103,000 – $174,000
Secure AI Engineer / AI Security Architect
$234,000
Median salary
Range: $179,000 – $289,000
Source: Glassdoor.com
AI Model Risk Specialist
$140,500
Median salary
Range: $105,000 – $176,000
Source: Glassdoor.com
AI Risk & Assurance Specialist
$140,500
Median salary
Range: $105,000 – $176,000
Source: 6figr.com
Security Program Manager (AI Security)
$183,000
Median salary
Range: $146,000 – $220,000
AI Product Security Manager
$195,000
Median salary
Range: $151,000 – $239,000
*Note All salary information is based on aggregated market data from publicly available sources and reflects US estimates. Actual salaries may vary based on location, education and other qualifications, skills showcased during the interview, and other factors.
C|OASP PROGRAM FAQs
FREQUENTLY
ASKED
QUESTIONS
What is the Certified Offensive AI Security Professional (C|OASP) certification?
C|OASP is EC-Council’s offensive AI security program 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 attackers do.
Who should take the C|OASP certification?
C|OASP is ideal for red-team and blue-team professionals, SOC analysts, penetration testers, AI/ML engineers, DevSecOps specialists, and compliance managers responsible for AI safety in regulated industries like finance, healthcare, and defense.
What this program covers?
This program covers prompt injection attacks, model extraction and theft, training data poisoning, agent hijacking, LLM jailbreaking, and defensive engineering techniques. The curriculum is aligned with industry frameworks, including OWASP LLM Top 10, NIST AI RMF, and ISO 42001.
Do I need prior cybersecurity experience?
Yes, this program requires foundational cybersecurity knowledge. This is not a beginner course, it’s hands-on offensive security training for professionals who already understand security fundamentals.
What's included in the certification?
The program includes 10 comprehensive modules, hands-on adversarial labs with real AI systems, DCWF-aligned learning paths, certification exam, lifetime access to materials, and access to the AI security community.