Cloudryption
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Cloud Security Decision Engine

See. Prioritize. Decide.

Cloudryption connects cloud findings, identities, data exposure, workloads, and attack paths into one decision model — so security teams can prioritize the fixes that reduce the most real risk.

Move beyond alert noise. See the complete exposure picture. Make decisions backed by evidence.

Explore Platform

Unified Visibility

See across identities, workloads, data, apps, and infrastructure.

Risk Prioritization

Focus on the attack paths, exposures, and risks that matter most.

Secure Control

Turn complex findings into clear remediation and policy action.

Built for Enterprise

Scalable, extensible, and designed for complex cloud environments.

How Cloudryption Works

From Cloud Evidence to Security Decisions

Cloudryption does not treat findings as isolated alerts. It connects configuration, identity, network, workload, and data signals into a decision graph that helps teams understand what is exposed, why it matters, and which fixes reduce the most risk.

1

Collect cloud evidence

Read-only discovery of cloud configuration, identities, network topology, workloads, and security findings across your environment.

2

Normalize findings and assets

Standardize cloud signals, security findings, and asset metadata into a common evidence format, regardless of cloud provider.

3

Connect identities, network paths, workloads, and data stores

Build a decision graph that shows how cloud assets relate — which identities can access which resources, how exposure flows through the environment, and where sensitive data is reachable.

4

Identify crown-jewel exposure

Highlight the assets that matter most to your business and show which attack paths lead to them.

5

Prioritize attack paths and minimum fix sets

Recommend the smallest set of remediation actions that reduce the most connected risk — not by finding count, but by measurable exposure reduction.

6

Produce executive and technical evidence reports

Generate board-ready risk narratives and detailed technical findings, both backed by the same evidence graph.

Trusted by design partners across regulated industries

Why Teams Choose Cloudryption

Cloud risk is connected.
Security findings are not.

Enterprise security teams face posture findings, identity exposure, workload vulnerabilities, and sensitive data risks across separate tools. Cloudryption connects these signals into one explainable attack-path model so teams can understand what matters first.

Fragmented findings

Evidence is spread across CSPM, CIEM, DSPM, CWPP, SIEM, and vulnerability tools — with no unified view of combined risk.

Hidden blast radius

One misconfiguration can chain through identities, workloads, and data. Most teams cannot see how far a weakness can reach.

Slow remediation decisions

Without knowing which fixes reduce the most risk, teams delay action or waste cycles on findings that do not matter.

Decision layer for CNAPP, CSPM, CIEM, DSPM, and cloud security findings

One decision layer for enterprise cloud security

CSPM

Cloud Security Posture

Cloud configuration and posture evidence across AWS, Azure, and GCP.

Evidence: misconfigurations, benchmarks, drift Outcome: posture visibility and compliance
CIEM

Identity & Permissions

Identity permissions, trust relationships, and privilege escalation paths.

Evidence: role bindings, trust policies, permission sets Outcome: least-privilege enforcement
DSPM

Data Security Posture

Sensitive data location, classification, and access exposure context.

Evidence: bucket ACLs, encryption, data type Outcome: data risk reduction
CWPP

Workload Protection

Workload exposure, runtime behaviour, and vulnerability signals.

Evidence: CVEs, image scans, runtime context Outcome: runtime risk reduction
Exposure

Exposure Validation

Confirms whether a technical weakness can translate into real business impact.

Evidence: reachability probes, network paths Outcome: confirmed exploitability signal
Paths

Attack Path Engine

Models attacker movement across cloud assets, controls, and identities.

Evidence: graph traversal, blast-radius modeling Outcome: prioritized attack path inventory
Fix

Remediation Engine

Recommends minimum fix sets that deliver maximum measurable risk reduction.

Evidence: before/after path simulation Outcome: measurable risk reduction
Exec

Executive Reporting

Translates technical cloud risk findings into board-level decision language.

Evidence: risk scores, reduction metrics Outcome: board-ready risk narrative

Enterprise Use Cases

Enterprise attack-path showcases

Critical

Public Exposure to Sensitive Customer Data

A public-facing workload can reach a storage bucket containing customer records through excessive workload identity permissions.

Before

  • 42 attack paths
  • 11 exposed identities
  • 3 sensitive data stores reachable

Recommended Fix Set

  • Restrict public access path
  • Limit workload role permissions
  • Enforce bucket access boundary

After

  • 5 attack paths remain
  • 88% risk reduction
  • Crown jewel exposure removed

Business outcome: Customer data exposure path removed before production impact.

High

Over-Permissive Identity Creates Privilege Escalation

A developer identity can assume a privileged production role because of weak trust policy conditions.

Before

  • 27 privilege paths
  • 6 toxic permission combinations
  • 4 production environments affected

Recommended Fix Set

  • Restrict role trust policy
  • Remove unused admin permissions
  • Require conditional access

After

  • 3 privilege paths remain
  • 79% risk reduction
  • Admin escalation path broken

Business outcome: Production privilege escalation chain contained.

Critical

Vulnerable Workload Becomes Data Access Path

A vulnerable workload can reach internal services and uses an identity with broad read access to sensitive databases.

Before

  • 18 workload-to-data paths
  • 2 critical vulnerabilities
  • 1 sensitive database exposed

Recommended Fix Set

  • Patch critical workload vulnerability
  • Segment internal route
  • Reduce service identity data permissions

After

  • 2 workload-to-data paths remain
  • 91% risk reduction
  • Sensitive database path removed

Business outcome: Critical workload compromise no longer leads to sensitive data access.

Interactive Platform Demo

Simulate remediation before changing production

Connected attack graph paths

Cloudryption correlates exposure, IAM trust, workload context, and data access to surface attacker-relevant routes that bypass isolated control views.

Platform Differentiators

Built for enterprise cloud risk decisions

  • Evidence-backed attack paths
  • Identity-to-data risk modeling
  • Crown jewel prioritization
  • Remediation impact simulation
  • Minimum fix set recommendations
  • Board-ready reporting
  • Multi-cloud architecture
  • Audit-ready evidence trail

About the Platform

About Cloudryption

Cloudryption is an enterprise cloud security platform built to help organizations move from alert-driven cloud security to decision-driven cloud risk reduction. The platform connects cloud infrastructure, identity, workload, and data exposure signals into an explainable attack-path model, helping teams understand what matters, why it matters, and which remediation actions deliver the highest risk reduction.

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Engage with Cloudryption

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