PhishFirewall Security Awareness Training is an AI-driven platform centered around "Lora," an autonomous AI agent that manages phishing simulations and security awareness training without requiring manual admin intervention. The platform applies behavioral science frameworks—including the Fogg Behavior Model (B=MAP), Spaced Learning Theory, and Situated Learning Theory—to drive measurable changes in user security behavior. Rather than delivering periodic, generic training sessions, it operates on a continuous feedback loop. Key operational mechanics include: - Behavioral Fingerprinting: Tracks micro-behaviors such as hover times, reporting speed, and past simulation performance to build individual user risk profiles. - Dynamic Training Intervals: Recalculates optimal learning windows per user based on risk profiles, replacing fixed monthly training schedules. - Hyper-Personalized Simulations: Generates role-specific phishing lures tailored to individual susceptibilities (e.g., authority bias, urgency, social media). - Just-in-Time Micro-Remediation: Delivers under-60-second contextual training immediately after a user makes a mistake. - Positive Reinforcement Model: 97% of interactions are framed positively to build a security-aware culture rather than using punitive approaches. - Micro-Content Delivery: Bite-sized training content is delivered directly to users' inboxes, requiring no LMS login. The platform targets both admin efficiency (autonomous scheduling, follow-ups, and reporting) and end-user engagement (frictionless, inbox-delivered content). It claims a sub-1% phishing click rate as a performance benchmark.