TechNow provides an array of courses to meet our customer's requirements.  Courses that do not fit into our major course categories and custom or specialized courses appear here.  

Here are courses about specilaized Software or Hardware:

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Course Overview:

This is an advanced course that assumes the attendee is a qualified security professional with experience using security tools and understands the concepts behind penetration testing. Courses that build up the expertise that enables a student to succeed in this course is Security+, CEH, CISSP, and any of the GIAC certifications. This course is completely hands-on and utilizes the BackTrack tool suite from backtrack-linux.org. The course covers, in detail, various attacks and tools that are contained in the BackTrack tool suite.

Attendees to TN-335: Advanced Penetration Testing Using Open Source Tools will receive TechNow approved course materials and expert instruction.

Dates/Locations:

No Events

Duration: 5 days

Course Objectives:

  • Information Security and Open Source Software
  • Operating System Tools
  • Firewalls
  • Scanners
  • Vulnerability Scanners
  • Network Sniffers
  • Intrusion Detection Systems
  • Analysis and Management Tools
  • Encryption Tools
  • Wireless Tools
  • Forensic Tools
  • More on Open Source Software

Prerequisites:

  • Experience in IT Security
  • Solid basic knowledge of networks and TCP/IP
  • Experience in command line under Linux and Windows is required

 

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DoD 8570 Training

The Department of Defense requires that all information assurance personnel must become compliant with IT and security certification standards.

DoD 8570 training, also called Information Assurance training, is available through TechNow to provide you with the certification that is required.  Your DoD 8570 training  ( information assurance training ) at TechNow will provide you with all of the courses necessary to receive your DoD 8570.01-M certification.

Ongoing open enrollment through TechNow is available for our DoD 8570.01-M courses.

Please review the full & updated DoD approved IA baseline certifications aligned to each category & level of the IA workforce.


 

 

For further information or to schedule for classes, call us at 800-324-2294

 

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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

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.