TN-575: Open Source Network Security Monitoring teaches students how to deploy, build, and run an NSM operation using open source software and vendor-neutral tools. No network is bullet proof and when attackers access your network, this course will show you how to build a security net to detect, contain, and control the attacker. Sensitive data can be monitored and deep packet and deep attachment analysis can be achieved. As organizations stand up a Security Operations Center (SOC) the enterprise NSM is the key ingredient to that SOC. This course not only teaches how to implement an NSM technologically, but how to effectively monitor an enterprise operationally. You will learn how to architect an NSM solution: where to deploy your NSM platforms and how to size them, stand-alone or distributed, and integration into packet analysis, interpret evidence, and integrate threat intelligence from external sources to identify sophisticated attackers. A properly implemented NSM is integral to incident response and provides the responders timely information to react to the incident. TN-575: Open Source Network Security Monitoring is a lab intensive environment with a cyber range that gives each student in-depth knowledge and practical experience monitoring live systems to include: Cisco, Windows, Linux, IoT, and Firewalls.
Attendees to TN-575: Open Source Network Security Monitoring class will receive TechNow approved course materials and expert instruction.
This Course is taught utilizing Security Onion or RockNSM as specified by the customer.
Dates/Locations:
No Events
Duration: 5 Days
Course Objective:
The focus of this course is to present a suite of Open Source security products integrated into a highly functional and scalable Network Security Monitoring solution.
Prerequisites:
Students should have a basic understanding of networks, TCP/IP and standard protocols such as DNS, HTTP, etc. Some Linux knowledge/experience is recommended, but not required
Course Outline:
Network Security Monitoring (NSM) Methodology
High Bandwidth Packet Capture Challenges
Installation of Security Onion
Use Cases (analysis, lab, stand-alone, distributed)
Resource Requirements
Configuration
Setup Phase I – Network Configuration
Setup Phase 2 – Service Configuration
Evaluation Mode vs. Configuration Mode
Verifying Services
Security Onion Architecture
Configuration Files and Folders
Network Interfaces
Docker Environment
Security Onion Containers
Overview of Security Onion Analyst Tools
Kibana
CapME
CyberChef
Squert
Sguil
NetworkMiner
Quick Review of Wireshark and Packet Analysis
Display and Capture Filters
Analyze and Statistics Menu Options
Analysis for Signatures
Analyzing Alerts
Replaying Traffic
3 Primary Interfaces:
Squert
Sguil
Kibana
Pivoting Between Interfaces
Pivoting to Full Packet Capture
Snort and Surricata
Rule Syntax and Construction
Implementing Custom Rules
Implementing Whitelists and Blacklists
Hunting
Using Kibana to Slice and Dice Logs
Hunting Workflow with Kibana
Bro
Introduction and Overview
Architecture, Commands
Understanding and Examining Bro Logs
Using AWK, sort, uniq, and bro-cut
Working with traces/PCAPs
Bro Scripts Overview
Loading and Using Scripts
Bro Frameworks Overview
Bro File Analysis Framework FAF
Using Bro scripts to carve out more than files
RockNSM ( * If Applicable)
Kafka
Installation and Configuration
Kafka Messaging
Brokers
Integration with Bro and FSF
File Scanning Framework FSF
Custom YARA Signatures
JSON Trees
Sub-Object Recursion
Bro and Suricata Integration
Elastic Stack
Adding new data sources in Logstash
Enriching data with Logstash
Automating with Elastalert
Building new Kibana dashboards
Production Deployment
Advanced Setup
Master vs Sensor
Node Types – Master, Forward, Heavy, Storage
Command Line Setup with sosetup.conf
Architectural Recommendations
Sensor Placement
Hardening
Administration
Maintenance
Tuning
Using PulledPork to Disable Rules
BPF’s to Filter Traffic
Spinning up Additional Snort / Suricata / Bro Workers to Handle Higher Traffic Loads
This course, TN-385: TCP/IP Analysis & Implementation, provides students with a comprehensive technical introduction to TCP/IP & the interworkings of TCP/IP application to UNIX, Linux and Windows in a network environment. This course begins by providing a comprehensive protocol stack analysis. It continues with extensive hands-on exercises needed to configure TCP/IP on UNIX and Windows based networks.
Attendees to TN-385: TCP/IP Analysis & Implementation will receive TechNow approved course materials and expert instruction.
Dates/Locations:
No Events
Duration: 5 Days
Course Objectives:
A thorough comprehension of each level of the protocol stack
Configuring UNIX & Windows to access internetworks
Configuring & setting up a Cisco router
Properly implementing subnets to avoid ongoing maintenance headaches
Routing & routing protocols, RIP, OSPF, and IGRP
How to troubleshoot a wide range of routing problems
All major TCP/IP application services including: FTP, TELNET, SNMP, NFS, DNS, DHCP, & WINS
How to avoid common internetworking problems
How to troubleshoot TCP/IP networks using protocol analysis techniques – snoop on Sun Workstation & Network Monitor on Windows.
How to design, build, configure, & manage TCP/IP internetworks
Applying a structured methodology for troubleshooting TCP/IP internetworks
ACL's on Cisco routers
Prerequisites:
Students should have good end-user skills in TCP/IP (FTP, TELNET, RLOGON, & MAIL).
The HCISPP is the only certification that combines cybersecurity skills with privacy best practices and techniques. It demonstrates you have the knowledge and ability to implement, manage, and assess security and privacy controls to protect healthcare organizations using policies and procedures established by the cybersecurity experts at (ISC)2. TechNows HCISPP Certification Boot Camp is a comprehensive review of Healthcare cybersecurity with privacy best practices & industry best practices.
Attendees to TN-8155: HCISPP Certification Preparation Seminar will receive TechNow approved course materials and expert instruction..
Date/Locations:
No Events
Course Duration: 5 days
Course Objectives:
Strategically focus your preparation for HCISPP Certification
Cover a broad spectrum of topics in the 7 domains of the HCISPP Common Body of Knowledge (CBK)
Gain knowledge on the Healthcare industry including third party relationships and health data management concepts
Identify applicable regulations, compliance frameworks, privacy principles and policies to protect information security
Develop risk management methodology and identify control assessment procedures
Audience:
The HCISPP certification is ideal for security professionals responsible for safeguarding protected health information (PHI). Take this HCISPP training course to prepare to manage and implement security controls for healthcare information. HCISPPs are instrumental to a variety of job functions: Compliance Officer, Information Security Manager, Privacy Officer, Compliance Auditor, Risk Analyst, Medical Records Supervisor, IT Manager, Privacy & Security Consultants, and Health Information Manager.
Certified AI Program Manager (CAIPM) is EC-Council’s professional certification for people responsible for owning AI decisions and driving execution: business, technology, data, and risk.
The Certified AI Program Manager (CAIPM) Course equips you with hands-on expertise across the full spectrum of AI tools, from conversational AI and image generation to code assistants and audio synthesis.
Participants will learn how to evaluate, deploy, and integrate AI tools into enterprise workflows, understanding not just how they work, but how to leverage them for maximum business impact. This course covers how to assess AI readiness across teams and processes, Prioritize AI use cases tied to business outcomes, Design adoption and rollout roadmaps , Coordinate delivery across cross-functional teams, implement governance, Responsible AI, and security controls , and how to track performance and ROI to prove value
By the end of the course, learners will be well-prepared to take the Certified AI Program Manager (CAIPM) exam and demonstrate the ability to own AI initiatives end to end , validate mastery of decision framing and trade-off analysis for AI initiatives and Apply governance, ethics, and risk management principles across the AI lifecycle.
Course Objectives:
•MLOps Principles: Model life cycle management for scalable, production-ready AI •Use Case Evaluation: ROI-driven assessment and prioritization of AI initiatives •AI Strategy Frameworks: Enterprise AI roadmapping, portfolio planning, and value prioritization •AI Investment Justification: Quantifying AI value, ROI, and mission impact for funding decisions •Change Management: Workforce enablement and stakeholder alignment •KPI Development: AI metrics, success indicators, and executive dashboards •AI Governance: Risk, ethics, compliance, and responsible AI principles •Vendor Evaluation: AI platform and tool selection aligned with enterprise needs
Dates/Locations:
No Events
Prerequisites:Familiarity with generative AI concepts, prompt engineering fundamentals, and AI workflows will help you succeed.