CT-415: CompTIA SecAI+

CompTIA SecAI+ is the first certification in CompTIA’s expansion series, designed to help you secure, govern and responsibly integrate artificial intelligence into your cybersecurity operations. You’ll build the skills to defend AI systems, meet global compliance expectations and use AI to enhance threat detection, automation and innovation—so you can strengthen your expertise and help keep your organization’s systems and data secure.

SecAI+ helps you build practical AI security and automation skills on top of your existing expertise, so you can secure AI deployments, use AI‑assisted security tools with confidence, and stay ready for the next step in your cybersecurity career.

Course Objectives:

  • Apply AI concepts to strengthen your organization’s cybersecurity posture
  • Secure AI systems using advanced controls and protections to safeguard data, models, and infrastructure
  • Leverage AI technologies to automate workflows, accelerate incident response, and scale security operations
  • Navigate global GRC frameworks to ensure ethical and compliant AI adoption across industries
  • Defend against AI-driven threats like adversarial attacks, automated malware, and malicious use of generative AI
  • Integrate AI securely into DevSecOps pipelines and enterprise security strategies.

Dates/Locations:

No Events

Prerequisites: Recommended experience: 3–4 years in IT and 2+ years hands-on cybersecurity; Security+, CySA+, PenTest+, or equivalent recommended

SecAI+ (V1) exam objectives summary

     Basic AI concepts related to cybersecurity (17%)

  • Explain core AI principles and terminology: Machine learning, deep learning, natural language processing, and automation.
  • Identify AI applications in security: Use cases for AI in threat detection, defense, and security operations. 
  • Recognize AI-driven threats: Automated phishing, polymorphic malware, adversarial machine learning, and malicious use of generative AI.

Securing AI systems (40%)

  • Implement security controls: Protect AI systems, data, and models using robust technical safeguards. 
  • Secure AI deployment environments: Apply best practices across on-premises, cloud, and hybrid infrastructures. 
  • Mitigate adversarial risks: Defend against attacks targeting AI models, data pipelines, and inference layers. 

AI-assisted security (24%)

  • Enhance detection and response: Use AI-driven tools to identify anomalies, detect threats, and accelerate incident remediation. 
  • Automate security workflows: Integrate AI for event triage, alert correlation, and response orchestration. 
  • Apply AI techniques in operations: Incorporate AI into threat modeling, behavior analysis, and continuous monitoring. 

AI governance, risk, and compliance (19%)

  • Understand regulatory frameworks: Identify global governance requirements and their implications for AI adoption. 
  • Integrate GRC into AI projects: Incorporate governance, risk management, and compliance practices throughout the AI lifecycle. 
  • Ensure responsible AI use: Apply ethical guidelines, legal standards, and industry frameworks such as GDPR and NIST AI RMF.

TN-905: Cyber Threat Intelligence Analysis

 

Course Overview:

TechNow has worked worldwide enterprise infrastructures for over 30 years and has developed demos and labs to exemplify the techniques required to demonstrate technologies that effectively support CTI.  This course integrates well with our courses TN-575: Open Source Network Security Monitoring and TN-865: Wireshark Network Traffic and Security Analysis .

TechNow develops Cyber Ranges and makes them available for conferences in support of annual meetings for Cyber Threat Response Teams.  Developing scenarios and reacting to them appropriately is a big part of the value in understanding the contexts required to comprehend valuable CTI.   As with many advanced TechNow security courses, there is a large hands-on ratio.  This course helps Cyber Protection Teams (CPT), Defensive Cyber Operations (DCO), and Mission Defense Teams (MDT) to collect, analyze and apply targeted cyber intelligence to defensive operations in order to proactively act on and tune response to attacks by cyber adversaries.  CPT, DCO, and MDT can take preemptive action by utilizing CTI, understanding CTI tools, techniques and procedures (TTPs) needed to generate and consume timely and relevant intelligence to improve resilience and prevention.

This course focuses on the collection, classification, and exploitation of knowledge about adversaries and their TTPs. .  MDT puts us close the mission and helps define the internal context to be analyzed against the CTI.  TechNow pushes the student to truly understand how to think about and use CTI to make a difference.

Attendees to TN-905: Cyber Threat Intelligence Analysis will receive TechNow approved course materials and expert instruction.

Date/Locations:

No Events

Course Duration: 5 days

Course Objectives:

  • Learn to comprehend and develop complex scenarios
  • Identify and create intelligence requirements through practices such as threat modeling
  • Utilize threat modeling to drive intelligence handling and practices 
  • Breakdown tactical, operational, and strategic-level threat intelligence
  • Generate threat intelligence to detect, respond to, and defeat focused and targeted threats
  • How to collect adversary information creating better value CTI
  • How to filter and qualify external sources, mitigating low integrity intelligence
  • Create Indicators of Compromise (IOCs) in formats such as YARA, OpenIOC, and STIX
  • Move security maturity past IOCs into understanding and countering the behavioral tradecraft of threats
  • Breaking down threats mapped against their tradecraft to tweak IOCs
  • Establish structured analytical techniques to be successful in any security role
  • Learn and apply structured principles in support of CTI and how to communicate that to any security role.

Course Prerequisites:

Comments

Latest comments from students

 

Liked the class?  Then let everyone know!

TN-909: Windows Forensic Analysis

 

Course Overview:

Windows Forensic Analysis is a hands-on course that covers digital forensics of the Microsoft Windows operating system.  The collection and analysis of data tracking user based activity that can be used for internal purposes or legal litigation.  TechNow has the student analyze many data images for various Windows operating systems, as current as Windows 8.1, Windows 10  in an environment that uses many Cloud technologies such as  Office365, Skydrive, Sharepoint, Exchange Online, and Windows Phone.

This is not death by power point. The course is aligned with digital forensic investigators and executing hands-on labs. Lecture and labs walk the student through the knowledge required to truly understand the mechanics of Windows Forensic Analysis.

Attendees to TN-909: Windows Forensic Analysis will receive TechNow approved course materials and expert instruction.

Date/Locations:

No Events

Duration: 5 days

Course Objectives:

  • Windows Operating System Components
  • Core Forensic Principles
  • Live Response and Triage-Based Acquisition Techniques
  • Windows Image Mounting and Examination
  • Memory, Pagefile, Filesystems
  • Data and Metadata
  • Profiling systems and users
  • Tracking USB and BYOD
  • Log and Registry Analysis
  • User Communications
  • Email Forensics
  • Browser Forensics
  • Reporting and  Presentation

Course Prerequisites:

  • Windows and Security Experience

Comments

Latest comments from students

 

Liked the class?  Then let everyone know!

 

 

TN-425: Certified Offensive AI Security Professional (C|OASP)

Certified Offensive AI Security Professional (COASP) validates the competencies required for practitioners who need to demonstrate offensive AI security skills, emulating adversaries, validating defenses, and leading red-team/blue-team exercises to keep AI resilient, reliable, and auditable

The Certified Offensive AI Security Professional (COASP) equips you to identify and neutralize AI-specific threats before attackers do. And Bridges security, engineering, and data science so controls exist across the full AI life cycle.

Participants will gain hands-on experience to perform end-to-end adversarial testing and deliver defensive validation evidence including the ability to simulate adversarial AI kill chains, Harden AI architectures by secure system prompts, context windows, tool integrations, RAG pipelines, and agent memory, Conducting AI security assessments aligned to MITRE ATLAS, OWASP LLM/ML Top 10, NIST AI RMF, and DoD Test & Evaluation practices , This course covers how to build SOC-ready capabilities for AI-focused detection logic, incident playbooks, and forensic procedures , & how to execute prompt injection, adversarial prompting , Assess AI supply-chain risk , Implement defensive engineering controls and Produce assurance and compliance artifacts.

By the end of the course, learners will be well-prepared to take the Certified Offensive AI Security Professional (COASP) exam and demonstrate the ability to exploit vulnerabilities in LLMs and agents, and build defense that survive real world attacks, learners will master offensive techniques that break AI before the attackers do.

 

Course Outline: 

01. Offensive AI and AI System Hacking Methodology

02. AI Reconnaissance and Attack Surface Mapping

03. AI Vulnerability Scanning and Fuzzing

04. Prompt Injection and LLM Application Attacks

05. Adversarial Machine Learning and Model Privacy Attacks

06. Data and Training Pipeline Attacks

07. Agentic AI and Model-to-Model Attacks

08. AI Infrastructure and Supply Chain Attacks

09. AI Security Testing, Evaluation, and Hardening

10. AI Incident Response and Forensics 

 

Prerequisites: 

TN-412: Artificial Intelligence Essentials (AI|E) 

 

Dates/Locations:

No Events