Purpose-Built AI
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"Trained on real attack data, not generic threat feeds."
AI that understands mobile-specific attack vectors.
AI Engineered Specifically for Mobile Threat Detection
Generic security AI is trained on network, endpoint, and malware data — not on the mobile-specific attack patterns that Factor defends against. MTAD's AI models were developed using real-world mobile attack data: actual spear phishing campaigns targeting mobile users, vishing call signatures, behavioral patterns of malicious apps, and indicators of surveillance-grade spyware.
The result is detection accuracy that purpose-built AI achieves and general-purpose tools simply cannot match.
Key Capabilities
Spear Phishing NLP Engine
Natural language models trained to detect socially engineered mobile phishing, including SMS, WhatsApp, and email.
Vishing Call Analysis
Audio and metadata analysis to detect impersonation attempts in real time during calls.
App Behavior Modeling
Dynamic analysis of installed app behavior to identify data exfiltration and unauthorized access.
Threat Intelligence Integration
Continuously updated with Factor's own threat research and global mobile threat feeds.
Low False Positive Rate
Precision tuning reduces alert fatigue while maintaining high sensitivity to real threats.
Explainable Detections
Every alert includes context explaining why the threat was flagged, enabling faster analyst response.