Palo Alto Networks Firewall Training Course Lab

Working with the TechNow lab for the PA-215: Palo Alto Networks Firewall Essentials FastTrack course has been nothing less than a techie's idea of fun.  When students come in we are immediatly configuring the Cisco 3750 switches for access ports, VLANS, and trunks.  We then cable the switch to the Palo Alto Networks Firewall.  Each student gets their own Palo Alto Firewall Pod of hardware and software.  What we find as fun is the VLAN environment, with an array of virtual machines hosted on an ESXi server that can really exercise the abilities of the Palo Alto Firewall.  The DMZ VLAN hosts virtual machines that support enterprise services and also potentialy vulnerable web services.  The Trust VLAN has Windows and Linux clients.  The UnTrust VLAN has Web services and a VM of Kali. The hardware Firewall is additionally connected to a Management VLAN.  All those VLANs are trunked into an ESXi server where the student also has a VM-Series Palo Alto Networks Firewall for High Availability.  

After configuring all the trunking, VLANs, and network interfaces we learn about the firewall and configure it for the lab environment.  Using Metasploitable and Kali/Metasploit nefarious penetration attempts are executed.  Using packet captures, custom APP-ID's  and custom signatures are generated.  Custom logging and reporting are created to similate and enterprise and assist the desired Incident Response.  It is always fun in a training environment to learn all about the controls available in a product, even though specific controls may not be used in the operational environment.  In the end we have a good understanding of the Palo Alto Networks Firewall.

TN-765: Automating Administration with Windows Powershell

 

Course Overview:

This course provides students with the fundamental knowledge and skills to use PowerShell for administering and automating administration of Windows servers. This course provides students the skills to identify and build the command they require to perform a specific task. In addition, students learn how to build scripts to accomplish advanced tasks such as automating repetitive tasks and generating reports. This course provides prerequisite skills supporting a broad range of Microsoft products, including Windows Server, Windows Client, Microsoft Azure, and Microsoft 365. In keeping with that goal, this course will not focus on any one of those products, although Windows Server, which is the common platform for all of those products, will serve as the example for the techniques this course teaches.

Attendees to TN-765: Automating Administration with Windows Powershell will receive TechNow approved course materials and expert instruction.

Date/Locations:

No Events

Course Duration: 5 days

Course Objectives:

 

  • Describe the functionality of Windows PowerShell and use it to run and find basic commands
  • Identify and run cmdlets for server administration
  • Work with Windows PowerShell pipeline
  • Describe the techniques Windows PowerShell pipeline uses
  • Use PSProviders and PSDrives to work with other forms of storage
  • Query system information by using WMI and CIM
  • Work with variables, arrays, and hash tables
  • Write basic scripts in Windows PowerShell
  • Write advanced scripts in Windows PowerShell
  • Administer remote computers
  • Use background jobs and scheduled jobs
  • Use advanced Windows PowerShell techniques

 

Course Prerequisites:

 

  • Experience with Windows networking technologies and implementation.
  • Experience with Windows Server administration, maintenance, and troubleshooting.

 

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

Course Description:

Artificial Intelligence Essentials (AIE) is a foundational AI literacy certification that builds practical understanding of AI and responsible use

The Artificial Intelligence Essentials (AIE) Course is designed to prepare learners for the newly Artificial Intelligence Essentials (AIE) exam. This hands-on program introduces professionals to core AI concepts, practical tools, and safe real-world applications. It equips learners to understand AI systems, use AI responsibly, and boost productivity across roles and industries

Participants will gain knowledge in understanding how AI systems work, where they are used, how they influence decision-making, and how they should be applied responsibly in everyday, professional, and organizational contexts. The course covers what AI is and what it is not, how data and models drive AI behavior, and how modern AI systems differ from traditional software. Learners develop the ability to interact effectively with AI tools, evaluate AI outputs with informed judgment, and apply responsible practices aligned with privacy, security, and global regulatory expectations.

By the end of the course, learners will be prepared to use AI confidently, safely, and productively while recognizing limitations, ethical risks, and broader societal impacts. It serves as a universal entry point before any technical, managerial, security, or governance specialization in AI.

Course Outline: 

01. Introduction to Artificial Intelligence

02. Everyday AI Tools and Use Cases

03. Building Blocks of AI

04. Prompt Crafting AI-Driven Interactions

05. AI Ethics and Responsible AI

Dates/Locations:

No Events

TN-535: Certified Forensic Computer Examiner (CFCE)

CCFE Core Competencies

  • Procedures and Legal Issues
  • Computer Fundamentals
  • Partitioning Schemes
  • Data Recovery
  • Windows File Systems
  • Windows Artifacts
  • Report writing (Presentation of Finding)
  • Procedures and Legal issues
  1. Knowledge of search and subjection and rules for evidence as applicable to computer forensics.
  2. Ability to explain the on-scene action taken for evidence preservation.
  3. Ability to maintain and document an environment consolidating the computer forensics.
  • Computer Fundamentals
  1. Understand BIOS
  2. Computer hardware
  3. Understanding of numbering system (Binary, hexadecimal, bits, bytes).
  4. Knowledge of sectors, clusters, files.
  5. Understanding of logical and physical files.
  6. Understanding of logical and physical drives.
  • Partitioning schemes
  1. Identification of current partitioning schemes.
  2. Understanding of primary and extended partition.
  3. Knowledge of partitioning schemes and structures and system used by it.
  4. Knowledge of GUID and its application.
  • Windows file system
  1. Understanding of concepts of files.
  2. Understanding of FAT tables, root directory, subdirectory along with how they store data.
  3. Identification, examination, analyzation of NTFS master file table.
  4. Understanding of $MFT structure and how they store data.
  5. Understanding of Standard information, Filename, and data attributes.
  • Data Recovery
  1. Ability to validate forensic hardware, software, examination procedures.
  2. Email headers understanding.
  3. Ability to generate and validate forensically sterile media.
  4. Ability to generate and validate a forensic image of media.
  5. Understand hashing and hash sets.
  6. Understand file headers.
  7. Ability to extract file metadata from common file types.
  8. Understanding of file fragmentation.
  9. Ability to extract component files from compound files.
  10. Knowledge of encrypted files and strategies for recovery.
  11. Knowledge of Internet browser artifacts.
  12. Knowledge of search strategies for examining electronic
  • Windows Artifacts
  1. Understanding the purpose and structure of component files that create the windows registry.
  2. Identify and capability to extract the relevant data from the dead registry.
  3. Understand the importance of restore points and volume shadow copy services.
  4. Knowledge of the locations of common Windows artifacts.
  5. Ability to analyze recycle bin.
  6. Ability to analyze link files.
  7. Analyzing of logs
  8. Extract and view windows logs
  9. Ability to locate, mount and examine VHD files.
  10. Understand the Windows swap and hibernation files.
  • Report Writing (Presentation of findings)
  1. Ability to conclude things strongly based on examination observations.
  2. Able to report findings using industry standard technically accurate terminologies.
  3. Ability to explain the complex things in simple and easy terms so that non-technical people can understand clearly.
  4. Be able to consider legal boundaries when undertaking a forensic examination

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.