Looking for Cyber Threats Through Statistical Outliers
Updated: For those who missed the webinar, you can watch here or read the transcript
Defenders of IT infrastructures complain that detecting malware is hard — but so it is for malware to hide. Malicious programs have to leverage the same computing hooks to run on a system, so they necessarily leave specific traces and artifacts. Arc4dia’s SNOW offers a few features that facilitate sleuthing for these artifacts.
In this webinar:
1. We will present SNOW’s database of objects.
2. We will show how we can look for outliers on a host, objects rarely seen across a given network.
3. We will demonstrate how to look for outlier relationships between objects, which may uncover malware even when it sneaks into common files and directories.
This Webinar is FREE but space is limited, so please REGISTER TODAY!
About the Speaker:
Justin Seitz is a Hunter @Arc4dia, has written books “Black Hat Python” & “Grey Hat Python”, Creator of @Hunchly. Blogging & training #OSINT techniques.
Recorded webinar will be distributed to all REGISTERED after the webinar session.
Updated: For those who missed the webinar, you can watch here or read the transcript
