Abnormal AI Reveals the Growing Risk of Human Error in Enterprise Email

Abnormal AI, the leader in AI-native human behavior security, today released a new research report, 2025 State of Misdirected Email Prevention: Keeping Sensitive Data Out of the Wrong Inboxes, reveali...

Autore: Business Wire

98% of security leaders consider misdirected email a significant risk-surpassing even malware and credential theft

LAS VEGAS: Abnormal AI, the leader in AI-native human behavior security, today released a new research report, 2025 State of Misdirected Email Prevention: Keeping Sensitive Data Out of the Wrong Inboxes, revealing that one of the most damaging and overlooked risks in enterprise cybersecurity comes not from malicious attackers, but from human mistakes.

Based on a survey of more than 300 security and IT professionals, the report highlights the growing prevalence and business impact of legitimate messages sent to the wrong recipient-also known as misdirected emails-which can result in data breaches, regulatory violations, remediation costs, and reputational damage.

The research makes clear that this concern is more than theoretical. Ninety-eight percent of security leaders consider misdirected email as a significant risk when compared to other risks like malware and insider threats. And those fears are being realized with 96% of organizations surveyed experiencing data loss or exposure from misdirected email in the past year, with 95% reporting measurable business impact such as remediation costs, compliance violations, or damage to customer trust.

“This report offers a sobering realization,” said Mike Britton, CIO at Abnormal AI. “The same inboxes attackers target are also the source of accidental data loss within organizations. Enterprises have invested heavily in stopping inbound threats like phishing, but outbound email remains a major vector for human error-one that has historically been overlooked.”

Additional findings include:

The research underscores the pitfalls of traditional email security and DLP tools, built to detect external attacks-not the unintentional data loss caused by internal human error. Behavioral AI, by contrast, models typical communication patterns and can identify deviations that indicate misdirected emails, stopping dangerous activity in its tracks by intervening before sensitive data leaves the organization.

“This is a visibility problem as much as it is a technology one,” Britton added. “Traditional tools can’t differentiate a legitimate customer email from a sensitive message going to the wrong recipient. Protecting data today requires more than defending against external threats-it means understanding and supporting human behavior. Organizations that integrate AI-driven insights with user-centric safeguards are better positioned to prevent mistakes from turning into breaches.”

Additional Resources:

About Abnormal AI:

Abnormal AI is the leading AI-native human behavior security platform, leveraging machine learning to stop sophisticated inbound attacks and detect compromised accounts across email and connected applications. The anomaly detection engine leverages identity and context to understand human behavior and analyze the risk of every cloud email event-detecting and stopping sophisticated, socially-engineered attacks that target the human vulnerability.

You can deploy Abnormal in minutes with an API integration for Microsoft 365 or Google Workspace and experience the full value of the platform instantly. Additional protection is available for Slack, Workday, ServiceNow, Zoom, and multiple other cloud applications. Abnormal is currently trusted by more than 3,200 organizations, including over 20% of the Fortune 500, as it continues to redefine how cybersecurity works in the age of AI. Learn more at abnormal.ai.

Fonte: Business Wire


Visualizza la versione completa sul sito

Informativa
Questo sito o gli strumenti terzi da questo utilizzati si avvalgono di cookie necessari al funzionamento ed utili alle finalità illustrate nella cookie policy. Se vuoi saperne di più o negare il consenso a tutti o ad alcuni cookie, consulta la cookie policy. Chiudendo questo banner, acconsenti all’uso dei cookie.