In the heat of a crisis, every keystroke counts, and indecision could cost your organization millions. What separates security pros from security liabilities? A plan – and practice.
Join Networking For Future (NFF) and the Cisco Security Team for this complimentary hands-on Threat Hunting Workshop ” on Thursday, October 1, 2020, from 9:00 a.m. to 2:00 p.m. ET to help enhance your knowledge, improve your skills, and test your abilities. The Threat Hunting Workshop is intended for everyone who has a need to use threat hunting skills.
This breakthrough interactive experience rejects the typical, boring webinar format. You are immediately hands-on, responding to dynamic attacks, containing incidents that organizations face every day.
In the Threat Hunting Workshop, you will:
- Uncover best practices for threat hunting
- Learn how to incorporate threat hunting into your daily workflow
- Network with your peers to share strategies and techniques
- Execute seven real-world dynamic attack lab scenarios
WHEN
Thursday, October 1, 2020, from 9:00 AM to 2:00 PM ET
WHERE
This is an online Webex event. Space is limited to the first 50 registrants.
WHO SHOULD ATTEND
Threat Hunting Workshops are intended for everyone. The goal is not to sell products, but to teach the concepts and techniques of threat hunting using a unified, cloud-hosted set of threat data integrated across endpoint, DNS, threat research, and cloud security tools.
WHAT ARE THE SKILL REQUIREMENTS
You do not need an in-depth understanding of security operations or Cisco security products. The labs provide an easy-to-follow, step-by-step guide to understanding today’s threat landscape and successfully securing your network before, during, and after an attack. Access to all the required products and tools will be provided.
All students completing the workshop will earn eight (8) CPE credits and receive a certificate of completion.
A secondary device is highly encouraged.
We’re looking forward to seeing you online.
Questions or Comments? Contact: marketing@nffinc.com
