ELTON rates each vulnerability in isolation, then lets the dependency graph decide what is actually exploitable. Vulnerability triage becomes structural: the graph separates what is exploitable from what is an internal weakness. Entry vectors produce conditions. Findings require them.
ELTON computes an attack graph over the digital twin. Entry vectors produce conditions, findings require them. Remediate a root and watch the conditional chain collapse along with your team's workload.
CVSSv4 introduced subsequent-system impact for a reason: real attacks chain. A low-severity information leak plus a reachable authentication bypass plus a memory-safety bug is not three medium problems. It is one critical path. ELTON models the whole path, scores the chain, and tells your developers which single root fix breaks the most.
ELTON maps each device's unique initial access points and traces exploit chains across components, interfaces, and trust boundaries to find realistic paths.
ELTON automates CVSSv4 subsequent impact by modeling trust relationships to determine what else falls if a component is fully compromised.
See whether fixing one vulnerability reduces the severity of the rest, before you ship the mitigation.
The graph shows which conditions hold every chain up. Remediation Optimization takes it from there: the fewest fixes that collapse the most exploitable severity, proven in a what-if before anyone writes code.
Start with one device. We build the twin from documentation your quality system already produces, run AI discovery remotely, and show you the graph: the handful to fix, and the evidence for everything else.
Three classes the dependency graph assigns. A direct finding is exploitable on its own from a known entry vector, and those are the roots worth fixing first. A conditional finding is real but reachable only while a root keeps producing the condition it requires. A weakness has no path on this device and ships dismissed with its reasoning.
By modeling trust relationships in the graph to determine what else falls if a component is fully compromised. Attack-path analysis first maps the device's own initial access points and traces exploit chains across components, interfaces and trust boundaries. The result is a realistic path, scored as one chain rather than as separate findings.
A device carrying serious defects that nothing can currently reach. Behind a locked kiosk interface the operating system may hold critical CVEs while the containment holds, so the device is not exploitable. It is fragile. The day a user interface breakout ships, the same defects with the same scores become exploitable.
Yes. The graph recomputes as new vulnerabilities surface, promoting weaknesses to vulnerabilities and back, with the evidence attached each time. A weakness is not closed and forgotten. It is a finding whose enabling condition is unmet today, and the platform tracks the condition rather than the assumption.
Yes. New-release simulation shows whether fixing one vulnerability reduces the severity of the rest before the mitigation ships. Toggle an entry vector or remediate a root in the model and the chain below it collapses, which is what tells a developer which single fix is worth the sprint.