Static, template-driven programs no longer reflect how modern social engineering actually works.
Legacy simulations rely on fixed templates that fail to reflect modern tactics such as QR phishing, MFA-bypass flows, and AI-enabled impersonation.
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Program administration remains unnecessarily resource-intensive, requiring significant time to build, launch, and maintain campaigns.
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Employees tend to memorize training signals, creating false confidence while real attacks slip through.
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Scenarios are rarely grounded in how the organization operates, making simulations less credible and less relevant to actual risk.
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Defenders remain static, while threat actors leverage AI at scale. Defenders remain static, while threat actors leverage AI at scale.Defenders remain static, while threat actors leverage AI at scale.
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Repetitive, generic training that users learn to ignore over time. Repetitive, generic training that users learn to ignore over time. Repetitive, generic training that users learn to ignore over time.
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AI that learns from every interaction, adapts to every challenge, and grows stronger with your workflow — so you're always one step ahead.
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Models modern social engineering techniques, including QR phishing, MFA-bypass flows, liquid/direct attacks, and AI-enabled impersonation using LLM-powered scenario generation.
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Uses agentic AI to understand your business, operating environment, and organizational context to generate scenarios that feel relevant, credible, and context-aware.
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Combines OSINT, organizational signals, and threat intelligence to create high-fidelity lures, messaging, and attack narratives grounded in real-world attacker workflows.
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Continuously analyzes user behavior, susceptibility patterns, and response history to improve targeting, refine simulations, and strengthen human risk modeling over time.
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Evaluates how users respond to authority, urgency, reward, and pressure to measure real decision-making under realistic social engineering conditions.
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Uses AI-driven personalization to tailor delivery, tone, attack path, and difficulty based on each user’s role, exposure, and behavioral profile.
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Applies LLMs and agentic AI across generation, targeting, optimization, and outcome analysis, enabling the platform to improve with every campaign cycle.
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Supports both fully autonomous, agentic execution and admin-led campaign control, giving teams flexibility across different operating models and program maturity levels.
Two powerful products, driven by one intelligent engine built to find, simulate, and eliminate threats across every attack surface your organization faces.
FULLY AUTONOMOUS
Replicates how a real attacker would operate by using OSINT to gather context, generate the scenario, target the user, and execute the simulation with no admin input.
ADMIN-CONTROLLED
Gives security teams full control over campaign creation and execution, with stronger templates, richer metrics, and optional AI-generated campaigns when needed.
Fraus helps organizations reduce user susceptibility, strengthen threat recognition, drive sustained behavior change, and improve risk visibility over time.
Fewer users fall for realistic, adaptive simulations as exposure and resilience improve over time.
Users become better at identifying, escalating, and reporting suspicious activity across attack scenarios.
High-risk users show sustained improvement through targeted, continuously adaptive reinforcement.
Risk insights give security teams a clearer view of overall risk across the organization based on modern threat landscape.
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