The introduction to SQL Databases training course is designed to train the learners on the fundamentals of database concepts. You will not only learn about the different types of databases, the languages and designs as well as describe important database concepts using SQL Server 2016. Anyone who is moving into a database role will benefit from taking this course.
Attendees to MS-5002: Introduction to SQL Databases will receive TechNow approved course materials and expert instruction.
Learn to protect yourself and your company against hackers, by learning their tools and techniques, and then testing your network. This course is heavily based on Kali and primarily on Metasploit. In TN-515: Implementing Cybersecurity and Information Assurance Methodologies class you will learn the step by step process that hackers use to assess your enterprise network, probe it & hack into it, utilizing a mixed-platform target environment including Windows, Linux, Solaris, and Cisco. This course is 90% hacking, but defenses for demonstrated hacks will be discussed. If you want to know the ins and outs of the hacks presented in this course, then this is the course for you.
Attendees to TN-515: Implementing Cybersecurity and Information Assurance Methodologies Class Attendees will receive TechNow approved course materials and expert instruction.
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
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