Scanner Validation and Noise Reduction

Your scanner found 10,000 things.
An attacker can use a handful of them.

SpartanX imports from the tools you already run and proves what is actually exploitable, cutting the noise so your team fixes what matters.

150+ integrationsProve exploitabilityLess noise
The problem

The noise problem

Scanners are good at finding potential issues and terrible at telling you which ones matter. The result is a backlog of thousands of alerts, most of them theoretical, all of them demanding attention.

Your team burns weeks triaging by CVSS and gut feel. The real exploitable path hides in the pile, and the false positives keep everyone busy chasing ghosts.

How it works

How scanner validation works

01

Import from your tools

Pull findings from 150+ tools including Tenable, Qualys, Rapid7, Wiz, and Snyk. Keep the stack you have.

02

Attack-validate each one

Targeted Attack Validation runs a real adversary against imported findings to confirm what is genuinely exploitable in your environment.

03

Chain for real impact

Flaws get chained across surfaces so you see which low-severity items combine into a real attack path to the data at risk.

04

Reprioritize by proof

Findings are scored 0 to 100 by validated business impact, not raw CVSS, so the queue reflects actual risk.

The outcome

What you get

A queue you can trust

Up to 95% less alert noise means your team works proven risk instead of theoretical lists.

Keep your stack

This works alongside the scanners you own. It makes them sharper instead of replacing them.

Impact-based priority

A validated 0 to 100 score by business impact tells you what to fix first, and why.
What it ends

It ends the weeks of manual triage spent guessing which scanner alerts are real.

Up to 95% less alert noise
150+ integrations
Near-zero false positives on confirmed findings

Cut the noise

Import your scanner output and see what an attacker can actually use.