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Programme Detail

Certified Offensive AI Security Professional

The Certified Offensive AI Security Professional programme develops advanced skills for using AI in offensive-security work and for testing AI-enabled systems. It covers...

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Offensive AI SecurityBy Enquiry

Programme overview

The Certified Offensive AI Security Professional programme develops advanced skills for using AI in offensive-security work and for testing AI-enabled systems. It covers AI-assisted reconnaissance, vulnerability discovery, automation, LLM and model attacks, adversarial machine learning, red teaming, and safe reporting. Participants will practise authorised security testing in controlled environments, moving from planning and discovery to technical validation, evidence capture, risk analysis, and professional reporting.

Programmes can be delivered via

HRD Corp Claimable
Yayasan Peneraju aligned
EC-Council

At a glance

Course code
EC-017
Provider
EC-Council
Category
Offensive AI Security
Status
By Enquiry
Duration
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Price
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What participants should gain

  • Use AI to accelerate authorised security testing and analysis
  • Assess vulnerabilities in AI, machine-learning, and LLM systems
  • Perform adversarial testing against models, prompts, data, and integrations
  • Automate offensive-security workflows while maintaining control and evidence
  • Report AI-security findings and recommend appropriate safeguards

Participant readiness

  • Strong ethical-hacking and penetration-testing knowledge
  • Experience with scripting, Python, or security automation is recommended
  • Basic understanding of machine learning and generative AI is beneficial

Who this course is for

  • Ethical hackers, penetration testers, red-team members, security consultants, and assessors
  • Network, application, cloud, or security professionals developing offensive-testing capability
  • Professionals working only within formally authorised and controlled testing environments

How the course is delivered

This programme will be conducted through interactive lectures, demonstrations, guided labs in isolated environments, controlled attack scenarios, evidence collection, group discussions, reporting exercises, and a final practical assessment.

This programme will be conducted through interactive lectures, demonstrations, guided labs in isolated environments, controlled attack scenarios, evidence collection, group discussions, reporting exercises, and a final practical assessment | By enquiry

Course outline

Module and topic breakdown

Module 1: AI and Machine Learning Foundations for Offensive Security

Authorised adversarial testing objectives, scope, safety, methodology, evidence, and communication

Module 2: AI-Assisted Reconnaissance and Attack-Surface Mapping

Passive and active information gathering on systems, users, applications, and infrastructure

Module 3: AI-Driven Vulnerability Discovery and Prioritization

Core concepts, terminology, and purpose of AI-Driven Vulnerability Discovery and Prioritization

Module 4: AI-Assisted Exploit Research and Development

Vulnerability root cause, affected component, preconditions, primitives, and exploitation constraints

Module 5: Automation of Penetration Testing Workflows

Identifying repeatable tasks, inputs, decisions, outputs, dependencies, and control points

Module 6: Generative AI, Prompt Injection, and LLM Application Attacks

Prompt components: role, objective, context, constraints, examples, and output format

Module 7: Adversarial Machine Learning and Model Evasion

Adversarial examples, evasion, poisoning, backdoors, extraction, inference, and privacy attacks

Module 8: Data Poisoning, Model Extraction, and Privacy Attacks

Preconditions, attack paths, tools, techniques, and indicators associated with Data Poisoning, Model Extraction, and Privacy Attacks

Module 9: Red Teaming AI Systems and Autonomous Agents

AI red-team objectives, scope, system mapping, threat models, test plans, and safety controls

Module 10: AI-Enabled Social Engineering and Synthetic Media Risks

AI-generated text, voice, images, video, profiles, and personalised influence content

Module 11: Securing AI Pipelines, APIs, Plugins, and Integrations

Core concepts, terminology, and purpose of Securing AI Pipelines, APIs, Plugins, and Integrations

Module 12: Operational Safety, Governance, Evidence, and Reporting

Governance structures, policies, decision rights, accountability, and oversight committees

Assessment and completion

  • Continuous knowledge checks and facilitator feedback throughout the programme
  • Completion of guided exercises, scenarios, labs, or case-study activities applicable to the course
  • Final review or practical activity to confirm understanding of the stated course objectives
  • Official EC-Council examination and certification requirements depend on the selected training package and current exam version

Availability

This programme currently requires an enquiry for pricing, scheduling, and delivery arrangements.

Programme enquiry

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