TN-812: Information Systems Security Engineering Professional (ISSEP)

Course Overview:

This concentration was developed in conjunction with the U.S. National Security Agency (NSA) providing an invaluable tool for any systems security engineering professional. CISSP®-ISSEP is the guide for incorporating security into projects, applications, business processes, and all information systems. Security professionals are hungry for workable methodologies and best practices that can be used to integrate security into all facets of business operations. The SSE model taught in the IATF portion of the course is a guiding light in the field of information security and the incorporation of security into all information systems.

Attendees to TN-812: Information Systems Secuirty Engineering Professional (ISSEP) will receive TechNow approved course materials and expert instruction.

Dates/Locations:

No Events

Duration: 5 Days

Course Objectives:

  • Systems Security Engineering
  • Certification and Accreditation
  • Technical Management
  • U.S. Government Information Assurance Governance

Prerequisites:

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User: fsarisen

Instructor comments: Thank you Tim for all the great information! I am confident that I'll do well on the ICND exam.

User: storoy30

Instructor comments: The instructor, Tim Burkard, was very knowledgeable on the course material and skilled at explain more complex ideas.

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TN-949: Certified Firewall Analyst Course

Course Overview:

This is a hands-on course that covers many of the concepts of securing the perimeter of an organization. This includes concepts such as intrusion detection, packet filtering, and central logging.

A skills focus enables the student to better absorb the subject matter and perform better on the job.   This is not death by power point. The course is aligned with information assurance operators and executing hands-on labs. Lecture and labs walk the student through the knowledge required to truly understand the mechanics of Firewalls.

This course is an excellent precursor to PA-215 Palo Alto Firewall Essentials FastTrack.

Attendees to TN-949: Certified Firewall Analyst Prep will receive TechNow approved course materials and expert instruction.

Date/Locations:

No Events

Duration: 5 days

Course Objectives:

  • Analyzing Network and Wireless Design
  • Creating and Auditing a Rulebase
  • Firewall Assessment and Penetration Testing
  • Host-Based Detection and DLP
  • Incident Detection and Analysis
  • IOS and Router Security
  • IPv6 and ICMPv6
  • Log Collection and Analysis
  • NAT and Proxies
  • Netfilter IPtables
  • Network Access Control
  • Network-Based Intrusion Detection
  • Packet Filters and Inspection
  • Packet Fragmentation
  • Perimeter Concepts and IP Fundamentals
  • Securing Hosts and Services
  • TCP/IP Protocols
  • VPN Design and Auditing
  • VPN Implementation

Course Prerequisites:

  • GSEC or equivalent experience
  • UNIX, Windows, networking and security  experience
  • This is a hands-on skill course requiring comfort with command line interaction and network communications

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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: 

AIE

 

Dates/Locations:

No Events

VM-325: VMware View: Install, Configure and Manage

Course Overview:

This hands-on training course builds your skills in the VMware ViewTM suite of products: VMware View Manager, VMware View Composer, and VMware® ThinAppTM.  Based on customer specification, this course can be based on View 4.x or 5.x, and ThinApp 4.x or 5.x releases.

Attendees to VM-325: VMware View: Install, Configure and Manage will receive TechNow approved course materials and expert instruction.

At the end of this course, you should understand the features and operations of View and be able to:

  • Install and configure View components
  • Create and manage dedicated and floating desktop pools
  • Deploy and manage linked-clone virtual desktops
  • Configure and manage desktops that run in local mode
  • Configure secure access to desktops through a public network
  • Use ThinApp to package applications

Date/Locations:

No Events

Duration: 5 days

Course Objectives:

  • Module 1: Course Introduction
  • Module 2: Introduction to VMware View
  • Module 3: View Connection Server
  • Module 4: View Desktops
  • Module 5: View Client Options
  • Module 6: View Administratory
  • Module 7: Configuring and Managing Linked Clones
  • Module 8: Local-Mode Desktops
  • Module 9: Command-Line Tools and Backup Options
  • Module 10: Managing VMware View Security
  • Module 11: View Manager Performance and Scalability
  • Module 12: VMware® ThinAppTM

Prerequisites:

  • VM-315: VMware Infrastructure: Install, Configure and Manage
  • Experience in Microsoft Windows Active Directory Administration
  • Experience with VMware vSphereTM
  • Before attending the course, students must be able to perform the following tasks:
    • Create a template in VMware vCenterTM Server and deploy a virtual machine from it
    • Modify a template customization file
    • Open a virtual machine console in vCenter Server and access the guest operating system
    • Configure Active Directory services

 

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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.