Stop the full spectrum of email threats with behavioral AI that knows your people.
The average business email compromise attack costs organizations $137,132.
88% Likelihood of a BEC attack in any given week in 2024.
It takes an average of 258 days to identify and contain a breach.
Starting with a one-click API integration, Abnormal ingests thousands of identity, behavior, and content signals across platforms like email and SaaS applications to baseline normal employee and vendor activity. It detects advanced threats like BEC and VEC by uncovering subtle behavioral anomalies that traditional tools miss.

Abnormal analyzes inbound messages using AI trained to compare personal behaviors relative to historic patterns for every user. Abnormal automatically detects and remediates malicious emails in, reducing triage and SOC workloads. This frees up security teams to focus on strategic priorities—not repetitive tasks.

Every threat stopped is backed by clear, contextual evidence enriched with behavioral metadata. Analysts can investigate detection rationale, trace anomalous behaviors, and search historical events through detailed logs and visual timelines—all within a unified console.

Admins can easily set risk thresholds, remediation actions, and quarantine workflows to align with organizational policies. Abnormal’s unified interface consolidates Microsoft and Abnormal detections to centralize email threat management and integrates with SOAR tools to streamline incident response workflows.

Powered by behavioral AI, Abnormal continuously evolves by learning from user behavior, attack trends, and cross-tenant intelligence. It detects never-before-seen threats without relying on static IOCs or signatures, and requires no manual tuning, rule writing, or policy maintenance.

The realization of value was almost immediate—real-time visibility into attacks going on in the environment that are bypassing the traditional defenses. That context allowed ADT to start identifying threat trends while blocking them from employee inboxes.”