Detecting Vendor Impersonations Attacks with GreatHorn

GreatHorn’s advanced anomaly detection uses artificial intelligence, machine learning and data science to automatically learn legitimate communication patterns between senders and recipients, identifying the anomalous emails, attachments, and links.

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Behavioral Analytics

GreatHorn analyzes all communication patterns between senders and recipients using behavioral analytics within our AI and ML models, providing organizations with immediate detection and insight into anomalous emails.

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Relationship Strength

Strength of a sender’s individual relationship to the recipient, as well as a “friends of friends” system that accounts for the sender’s overall relationship with others in the recipient’s organization.

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display name spoofing

Spoofing Likelihood

Analysis for employee display name spoofs, domain spoofs, and domain look-alikes, including comparison against known email addresses, executive impersonation tactics, and email authentication standards.

Technical Fingerprints

Sophisticated analysis of domain reputation, sending IP, and header information, including determining variations in expected authentication results for DMARC, DKIM, and SPF.

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phishing attack content analysis

Content Analysis

Deep content inspection based on keywords, regular expressions (RegEx), attachments, and URLs, to identify common spear phishing tactics—wire transfer and W2 requests, credential theft attacks, business service impersonations—all without storing the content or the mail.

Communication Patterns

Establishes an understanding of communication patterns unique to a specific individual and a specific organization, such as email frequency, volume, recipients, sending patterns and more.

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Learn more about how GreatHorn uses adaptive threat analytics to more effectively identify impersonation attacks within Microsoft 365 and Google Workspace.
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Learn what advanced threats are currently getting through your existing email security and into your end users’ mailboxes.