CL-115: Red Hat OpenStack Administration I: Core Operations for Cloud Operators

 

Course Overview:

The focus of Red Hat OpenStack Administration I: Core Operations for Cloud Operators (CL110) will be managing OpenStack using both the web-based dashboard and the command-line interface, in addition to managing instances and installing a proof-of-concept environment using Red Hat OpenStack Platform (RHOSP) director. Essential skills covered in the course include configuring Red Hat OpenStack Platform (using the director UI); managing users, projects, flavors, roles, images, networking, and block storage; setting quotas; and configuring images at instantiation.

Attendees to CL-115 Red Hat OpenStack Administration I: Core Operations for Cloud Operators will receive TechNow approved course materials and expert instruction.

Dates/Locations:

No Events

Duration: 5 Days

Prerequisites:

This course is designed for Linux system administrators, cloud administrators, and cloud operators interested in, or responsible for, maintaining a private or hybrid cloud.

Prerequisites for this course is Red Hat Certified System Administrator (RHCSA) or demonstrate equivalent experience

Course Outline:

  • Launch an instance
  • Manage projects, quotas, and users
  • Manage networks, subnets, routers, and floating IP adresses
  • Create and manage block and object storage in the OpenStack framework
  • Customize instances with cloud-init
  • Deploy scalable stacks
  • Deploy RedHat OpenStack Platform using RHOSP director

 

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DoD 8570

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 availble 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:

Note: The Certifications in red are recently added to approved list as of 2/4/19

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

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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: 

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

 

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