Trustmi introduces enhanced Behavioral AI to target social engineering attacks

Trustmi today announced new Behavioral AI, anomaly detection, and risk-scoring capabilities to help enterprise customers combat social engineering attacks on their finance teams, payment systems, suppliers, and processes.

“Attackers are increasingly manipulating trusted individuals within organizations and among vendors using a new AI-powered toolkit. Coupled with massive, complex processes and siloed operations, businesses encounter a perfect storm of vulnerability,” said Shai Gabay, co-founder and CEO of Trustmi. “Our emphasis on safeguarding payment processes has allowed us to observe this rapid evolution. By integrating continuous monitoring, anomaly detection, and automated risk scoring, Trustmi’s behavioral AI provides a powerful layer of protection that directly addresses the human and psychological factors at the core of social engineering attacks.”

Trustmi’s new capabilities empower enterprise customers by integrating a behavioral AI engine with three data layers—vendor, employee/user, and payment fingerprint—to produce a comprehensive, contextual risk score tailored to roles with access to funds, such as finance teams and executives. Instant risk scoring prioritizes high-risk cases for immediate review. By integrating with various systems, Trustmi holistically evaluates threats, concentrating on bad actors’ primary goal of stealing money. It adapts to complex schemes and enhances detection using contextual data specific to financial transactions.

“What concerns me right now are elements outside my control, such as a compromised vendor. Our company, people, and systems may be secure, but someone else’s issue becomes my problem if a bad actor can access our systems via a compromised vendor. The complexity of threats has advanced dramatically over just a few years,” said Yuval Levinson, VP of Finance at AppsFlyer.