About CVEasy AI: Built by a Practitioner

The Origin Story

From frustration to foundation

Every vulnerability management tool on the market follows the same playbook: charge per asset, lock your data in someone else's cloud, and give you a CVSS score that tells you everything is critical.

We built CVEasy AI because that model is broken. Security teams don't need another dashboard that tells them everything is on fire. They need intelligence, context-aware, actionable, prioritized intelligence that helps them fix what actually matters, and they should not have to ship their most sensitive inventory to a third party to get it.

The application is a desktop app built with Tauri and Rust with a React front end, and the AI model runs on the device itself. It was designed to work fully offline, so teams on isolated or regulated networks can run the entire exposure management loop without a connection. Your vulnerability data is the most sensitive inventory you own, and it never leaves your network.

The Architecture of the Product

Three ideas the product is built around

Better prioritization

The True Risk Intelligence Score (TRIS) weighs a vulnerability against the context of the environment it lives in. Twelve layers, from exploit maturity to attack-path blast radius, so teams can focus on the small number of issues that actually put them at risk instead of triaging a long list by severity alone.

Validation before remediation

BASzy, the built-in attack simulation engine, checks whether a finding is genuinely exploitable in your stack before anyone spends time patching it. A blocked chain is evidence too: it documents the control that held and lowers the score.

Remediation as the goal

The AI assistant exists to close findings, not just report them. It rolls the underlying CVEs into a single work order and orchestrates remediation through the consoles you already run, including Intune, Jamf, Tanium, Automox, and PDQ Connect, with closed-loop verification on the next sync.

Founder

Chris Boker

Chris leads the engineering and product architecture. He created the TRIS scoring method and anchors a growing research portfolio around it. MS in Cybersecurity & Information Assurance with a thesis focus on risk-based vulnerability management, plus 20+ industry certifications earned over years of hands-on work in vulnerability management, penetration testing, and security operations.

Much of what is implemented in CVEasy comes from that practice: years in vulnerability management, building custom tooling to run cybersecurity for a family-owned business, and the theories developed over the course of the Master's degree. CVEasy is the platform he wanted to use, so he built it.

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Certifications

S+

Security+

N+

Network+

C+

CySA+

P+

PenTest+

A+

SSCP

AWS

AWS CCP

Azure (x3)

Google IT

ISC2 CC

L+

Linux+

ITIL v4

Mission

Democratize vulnerability intelligence.

Enterprise vulnerability management shouldn't scale your bill with your infrastructure. It shouldn't require sending your most sensitive data to someone else's cloud. And it shouldn't take a team of 10 to operate.

CVEasy AI puts AI-powered vulnerability intelligence, breach & attack simulation, and compliance automation on a single Mac. One payment. Your hardware. Your data. Forever.

CVEasy AI is forged in Milwaukee, Wisconsin: founded, designed, and built in the United States. Local first means it runs on your hardware, in your building, with no cloud in between.

We work with managed security providers, healthcare organizations, and enterprise security teams who need to keep their exposure data in house. We're building the CTEM platform we wished existed, and making it accessible to every security team, from startups to the Fortune 500.

Integrations & Compatibility

Works with the tools you already use.

Native API connectors pull from your scanners, EDR, AppSec, identity, and cloud tooling, file imports and push endpoints catch everything else, and remediation orchestrates through your patch consoles. 121 integrations across 16 categories in total.