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Description

Abnormal AI provides an innovative behavioral AI platform that defends against highly targeted and automated email threats such as phishing, social engineering, and account takeovers. By employing superhuman understanding of human behavior and anomaly detection, it stops AI-driven attacks that often bypass conventional security tools. The platform operates fully autonomously, detecting and neutralizing threats in milliseconds without requiring human intervention, which significantly reduces the workload on security teams. It integrates smoothly with cloud email services like Microsoft 365, offering multi-layered protection with minimal disruption. With more than 3,000 customers, including 20% of the Fortune 500, Abnormal AI has proven its ability to reduce phishing attacks by 90% and lower SOC headcount by 50%. Customers praise its fast implementation, ease of use, and strong customer support. Its AI agents also automate repetitive security operations center workflows, accelerating response times. This comprehensive solution is designed to protect humans by focusing on behavioral insights rather than relying solely on traditional rule-based detection.

Description

Silmaril is an innovative defense mechanism against prompt injection that autonomously heals itself, aiming to safeguard AI systems from sophisticated, multi-layered threats that conventional barriers cannot mitigate. Unlike traditional methods that merely filter inputs, it envelops inference calls, assessing whether the sequence of actions is steering towards a detrimental result. By employing a multihead classifier, it evaluates user intentions, application contexts, and execution states simultaneously, which allows it to identify indirect injections, multi-turn attack sequences, context manipulation, and tool exploitation before any harm can occur. To enhance its protective capabilities, Silmaril incorporates autonomous threat-hunting agents that explore systems, identify weaknesses, and produce synthetic training data based on actual attack incidents. These findings facilitate automatic model retraining, allowing for the deployment of updated defenses in less than an hour, while simultaneously disseminating anonymized protective measures across all instances. Moreover, this proactive approach ensures that the system remains resilient against emerging threats, adapting continuously to the evolving landscape of cybersecurity challenges.