February Updates from Adobe, Microsoft — Krebs on Security -
Do Software-Defined Data Centers Pose Security Concerns? - Dark Reading -
State-sponsored Spy Campaign Targets Ukrainian Infrastructure - Infosecurity Magazine -
New York State Unveils Strict New Cybersecurity Regulations - Infosecurity Magazine -
Closing The Cybersecurity Skills Gap With STEM -
Google was aware of Russian APT28 group years before others -
Business-Driven Security™ to Lead through Chaos -
Check out our CEO Idan Tendler in blumberg Capital
#RSAC: Maximizing Security Beyond Next Gen -
Yahoo Could Cut $250m Off Sale Price - Reports -

The Insider
Threat Problem

Stolen credentials. Rogue users. Careless employees. They all amount to one thing: insider threats. When legitimate accounts are abused or compromised, their behavior changes. Traditional security solutions don’t see it. Fortscale does.

User & Entity Behavior Analytics (UEBA) for Insider Threat Detection:

It’s Not Magic, it’s Just Really Good Math

Many UEBA solutions are primarily rules-engines with machine learning capabilities layered on top, limiting the threats they can identify to those that they can write a rule for, hindering scalability, and contributing to the noise of a SOC. Fortscale is not just another rules-engine. Fortscale has been designed from the ground up as a machine learning system that uses advanced computing and mathematics to detect abnormal account behavior indicative of credential compromise or abuse.

No rules to write. No limits on what Fortscale can find.

Don’t just take our word for it

Fortscale Was Named Gartner Cool Vendor

in UEBA, Fraud Detection, and User Authentication

Get Started Fast

Let’s discuss your needs and show you how Fortscale can work for you.