Email Security: Using ML to Prevent Advanced Attacks

Predictive AI: Central to Advanced Email Security

Machine learning is a subset of AI that’s focused on recognizing patterns and learning for data in order to make predictive business decisions. While there’s certainly plenty of hype around this topic — much of it wildly unrealistic and even scary — these technologies have very real, and very important, commercial applications for many category-leading companies today.

Defining ‘Good’ to Prevent Phishing Attacks

Unlike systems that scour the entire attack surface in search of attack events, the Agari Secure Email Cloud takes an identity-based approach that continuously detects and responds to threats in real time. Its central concept is simple. If an email isn’t known to be good, it may be bad — which is the exact opposite of systems that look for malicious signatures. It works because of a simple truth: While it’s the illegitimate email that generates headlines, the vast majority of all email sent around the planet is legitimate.

Using Machine Learning to Protect Organizations

In actual deployments, this approach functions with 99.9% efficacy against all advanced email attacks, including the hardest to detect account takeover-based scams. The Agari Secure Email Cloud uses this same graph-based approach to continuous detection and response in order to detect and remediate latent threats that evade early detection by physically removing them from the inbox. The technology also provides SOC teams with automated tools that reduce the time it takes to detect and remediate data breaches by up to 95%.



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Agari is the Trusted Email Identity Company™, protecting companies and people from phishing and socially-engineered email attacks.