Understand how our algorithm works to move beyond static scoring. Arakt uses stochastic modeling and advanced attack-path simulations to map how cyber risk cascades through your infrastructure, quantifying your exposure with actuarial precision.
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A six-stage process translating technical vulnerabilities into business-ready financial intelligence.
The engine ingests your specific firmographics, infrastructure topology, and security control efficacy. This is enriched with global threat intelligence and proprietary actuarial datasets on record-level loss magnitude.
We construct a dynamic risk graph that mimics real-world adversary behavior. The model maps every potential connection between assets, assigning transition probabilities based on your implemented security controls.
Using a 'Random Walk' algorithm, we simulate thousands of non-linear attack scenarios. The engine traverses the graph, testing how far an adversary can move before triggering a high-impact 'Damaging Node.'
Once a damaging node is reached, we calculate financial loss using an inverse log-normal distribution. This power-law model is critical for capturing 'Long Tail' risk—those low-frequency but catastrophic loss events.
The simulation runs tens of thousands of times per workspace. This massive-scale Monte Carlo iteration ensures that individual statistical anomalies are filtered out and the final risk results converge into a stable, reliable mean.
The final raw data is translated into executive-level insights. Users receive a clear view of their annual loss expectancy, optimal insurance coverage limits, and prioritized remediation plans based on ROI.
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