AI-Native Cyber Exposure Management With Financial Risk Quantification

Founded in 2012 and registered as Cyesec Ltd., the company sells continuous exposure management to enterprise security organizations in regulated and high-risk sectors, naming financial services, critical infrastructure, healthcare, technology and retail among its markets. Its buyers are CISOs, group security leaders, risk officers and GRC teams, and it also reaches smaller organizations indirectly through MSSPs and channel partners. The founding team, led by chief executive Reuven Aronashvili, came out of offensive security, enterprise defense and risk practice rather than pure product engineering.

Onboarding starts with an Industry Attack Graph that supplies day-one baseline visibility, after which the platform builds an organization-specific attack graph mapping real paths from exposed entry points to business-critical assets across on-premise, cloud and hybrid estates. Those findings feed a cyber risk quantification model that attaches a dollar cost to each path, so remediation is sequenced by exploitability and financial impact instead of CVSS score or vulnerability volume. Agentic assessments and automated simulations then validate whether the deployed controls actually hold.

Distinguishing the offering from scanner-led competitors is the pairing of software with embedded expert services, covering assessments, incident response and maturity uplift as an ongoing engagement rather than an add-on. Program maturity is benchmarked against NIST CSF 2.0, while a separate AI risk module scores organizations against the NIST AI RMF and surfaces shadow AI usage. Group-level rollups across subsidiaries suit multi-entity holdings and private-equity portfolios, and the vendor lists ISO 27001, ISO/IEC 42001, SOC 2 Type II and CREST credentials.