Heimdal Email Fraud Prevention

Utilizes machine learning and a vast number of analysis vectors to detect subtle fraudulent cues that traditional filters might miss.

Combines automated analysis with live threat intelligence to stay ahead of new and evolving scams.

Scans email content for language and phrasing typical of fraudulent attempts or scams.

Evaluates email attachments for potential malicious character and tracks any modifications.

Identifies and flags HTML templates or tags within an email that deviate from normal patterns.

Counts and identifies URLs that our detection engine has flagged as suspicious.

A neural network assesses whether the email content is designed as clickbait.

Compares the language used in an email with the typical languages used within the organization to detect anomalies.

Uses AI to identify and flag emails that are statistically unusual or "out-of-character" for a user's communication history.

Allows administrators to quarantine suspicious emails or tag their subjects with a warning label, giving them control over potential threats.

The system can retroactively identify malicious emails, ensuring no threat goes undetected.