TechNow has been involved in enterprise client server architectures since 1990.  TechNow has delivered  national and international implementations for Valero, Wholefoods, Quest, USAA, Golfsmith, AMD, Motorola, and many other fortune 1000 corporations, 

TechNow's training program has followed the evolution of enterprise computing into virtualization and cloud computing. With a focus on security, TechNow can present the ramifications of many centralized strategies.  All courses utilize enterprise instructors with experience and can discuss the detail of implementation and the integration into an existing infrastructure.

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Course Overview:

 

Install, configure, and manage Red Hat JBoss Enterprise Application Platform

Red Hat JBoss® Application Administration I teaches you the best practices for installing and configuring Red Hat JBoss Enterprise Application Platform 6. Through hands-on labs, learn the essential, real-world tasks that a system administrator needs to know to effectively deploy and manage applications on JBoss Enterprise Application Platform.

Attendees to RH-345: Red Hat JBoss Application Administration I, will receive TechNow approved course materials and expert instruction.

Dates/Locations:

Duration: 5 Days

Course Objectives:

  • Overview of JBoss Enterprise Application Platform
  • Configure JBoss Enterprise Application Platform in standalone mode
  • Configure JBoss Enterprise Application Platform in domain mode
  • Configure servers
  • Use the CLI tool
  • The datasource subsystem
  • The logging subsystem
  • The messaging subsystem
  • The security subsystem
  • JVM configuration
  • Migrating applications to JBoss Enterprise Application Platform 6
  • The web subsystem

Prerequisites:

  • Linux System Administration

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Course Overview:

This course will be fast paced with in-depth and live demonstrations.

Date/Locations:

No Events

Duration: 1 day

Course Objectives:

  • UEFI, SecureBoot, TPM, and Enterprise BitLocker
  • Windows VPN in the Enterprise
  • Windows Advanced Firewall
  • Utilizing Windows WMI
  • Administering Windows with Powershell
  • Using Autopsy for Forensics

Prerequisites:

 

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Course Overview:

This course will be fast paced with in-depth and live demonstrations.

Date/Locations:

No Events

Duration: 1 day

Course Objectives:

  • AIDE
  • DNS Security with DNSsec
  • Logging and Audit Management
  • Linux Security Modules and SE-Linux
  • Linus Containers (Jailing Services and Apps)
  • SSH and SSL tunneling

Prerequisites:

 

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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