Skip to main content
Intelligent Security Governance — 340+ Frameworks Powered by Ayurak AI
Unified Threat Workbench

Automated Threat Modeling Platform

The Unified Threat Workbench: Design, Analyze & Remediate in Minutes

The most advanced automated threat modeling platform for enterprise security teams. Upload architecture diagrams, analyze threats with AI using STRIDE, PASTA, LINDDUN, and MAESTRO, get code-level remediation, and map findings to 340+ compliance frameworks. From code commit to production.

STRIDE & MAESTRO
CI/CD Blocking
340+ Frameworks
Zero Config Setup

Threat Assessment

Live Pipeline Analysis

Engine:Ayurak v4.2
Framework CoverageTotal Threats: 85
STRIDE24
PASTA31
LINDDUN12
MAESTRO18
Top Priorities
2 Critical2 High
SQL Injection
CVSS 9.8Fix
XSS Reflected
CVSS 7.5Fix
CSRF Token
CVSS 5.2Fix
System Active
Last scan: 2m ago
Auto-Remediation

Ayurak automatically patched 12 vulnerabilities in commit #8f2a9

Vision to Ops

Predictive Threat Modeling

Move beyond static diagrams. Aristiun's Aribot engine continuously scans your architecture, identifies attack vectors, and generates dynamic threat models that evolve with your code. From high-level design vision to operational reality.

CI/CD Integration

Native plugins for GitHub, GitLab, and Azure DevOps to block risky commits.

Multi-Framework Support

Comprehensive coverage including STRIDE, PASTA, LINDDUN, and MAESTRO.

Automated DFD Generation

Visualize data flow diagrams automatically generated from your codebase.

Compliance Mapping

Map threats directly to NIST 800-53, SOC 2, and ISO 27001 controls.

STRIDEPASTALINDDUNMAESTROAttack TreesNIST 800-53MITRE ATT&CKGitHub ActionsAzure DevOpsGitLab CI
Interactive Demo

The Unified Threat Workbench

Click on any service node to inspect its threats, view attack paths, check compliance mappings, and read AI-generated remediation plans. Hit Scan to watch the engine analyze the architecture in real time.

PaymentGateway_V2.0High Risk
Auth Service
Express 4.18 · 2 threats
critical
Scan Activity Log
14:32:01Scan initiated: PaymentGateway_V2.0
14:32:03Discovered 8 services, 9 connections
14:32:05STRIDE analysis: 6 spoofing, 4 tampering, 3 info disclosure
14:32:08Critical: JWT algorithm confusion in Auth Service
14:32:10Critical: SQL injection in UserRepository.findByEmail()
14:32:12High: Stored XSS in Admin Dashboard ticket viewer
14:32:14Mapped 12 threats to 4 compliance frameworks
14:32:16Generated 5 AI remediation plans (avg confidence: 97.6%)
14:32:18Scan complete: 12 findings, 3 attack paths identified

How the Security Workbench Works

Bring your own diagrams, collaborate in real time, generate secure architectures with AI copilots, and manage living threat models with continuous compliance and cost insights.

01

Upload Your Diagrams

Import existing architecture diagrams in any format: Visio, Draw.io, Lucidchart, PNG, SVG, PDF, Terraform, CloudFormation, Kubernetes manifests, or OpenAPI specs. The workbench automatically parses and maps your architecture into an interactive threat model.

02

Collaborate & Draw

Work together with your team to draw and refine architecture diagrams directly in the workbench. Real-time collaboration lets architects, developers, and security engineers build diagrams together with role-based access and version history.

03

Generate with AI Copilots

Use the Architecture Generator and AI copilots to auto-generate secure, cost-effective architecture diagrams from natural language descriptions, code repos, or cloud infrastructure scans. The AI recommends security-hardened design patterns and flags risky configurations.

04

Manage Living Diagrams

Diagrams stay alive, synced to your real infrastructure. As your cloud environment, repositories, and APIs evolve, the workbench automatically updates your architectural models and re-evaluates threats in real time.

05

Ops Metrics & Cost Analysis

Track operational security metrics, infrastructure costs, and tool spend directly from your architecture view. Identify over-provisioned resources, redundant security tooling, and cost optimization opportunities alongside your threat posture.

06

Continuous Compliance, Threats & Cost

Every change triggers automated threat analysis using STRIDE, PASTA, LINDDUN, and MAESTRO frameworks. Compliance mappings to 340+ frameworks update continuously, with cost-impact analysis for every remediation recommendation.

Methodology Support

Choose the threat modeling framework that fits your organization, or combine them for complete coverage.

STRIDE

Microsoft's model covering Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, and Elevation of Privilege.

PASTA

Process for Attack Simulation and Threat Analysis, a 7-stage risk-centric methodology that aligns business objectives with technical requirements.

LINDDUN

Privacy-focused framework covering Linkability, Identifiability, Non-repudiation, Detectability, Disclosure, Unawareness, and Non-compliance.

MAESTRO

Patented

Patented AI-system threat model addressing Manipulation, AI-specific exploits, Evasion, Supply chain, Toxicity, Reconnaissance, and Operations. Purpose-built for LLM and ML pipeline security.

Attack Trees

Hierarchical decomposition of attack goals into sub-goals and leaf nodes representing individual attack steps with probability and cost.

Built for Engineering Teams

Every feature designed to integrate into your existing development workflow without disruption.

CI/CD Integration

Scan every pull request automatically. Block merges that introduce critical architectural flaws. Native support for GitHub Actions, GitLab CI, Azure Pipelines, and Jenkins.

Full-Stack Coverage

Model threats across application code, cloud infrastructure (IaC), container orchestration, API schemas, and data flows, all in a single unified graph.

Compliance Mapping

Automatically map identified threats to controls in NIST 800-53, ISO 27001, SOC 2, PCI DSS, HIPAA, and 340+ other frameworks.

Code-Level Remediation

AI generates specific, actionable fix suggestions with code snippets, library recommendations, and estimated implementation effort.

Data Flow Diagrams

Auto-generate DFDs from your codebase. Track how data moves between services, identify trust boundaries, and surface data exposure risks.

Drift Detection

Continuously compare deployed architecture against the last approved threat model. Get alerts when architectural changes introduce new risk.

Platform Innovation

The Unified Security Workbench

One always-current workspace where architecture, threats, code vulnerabilities, shadow AI, and compliance come together. Stop switching between 15 disconnected tools. Aristiun gives you one screen for your entire security posture.

Digital Twin

Digital Twin of Your Infrastructure

Aristiun ingests your full architecture: cloud infrastructure (AWS, Azure, GCP), Kubernetes clusters, CI/CD pipelines, APIs, databases, and third-party integrations. The result is an always-current digital twin. Every change in your real environment is reflected automatically, so threats are validated against what actually exists, not what was documented months ago.

Code ↔ Threat

Code-Level Threat Validation

How does a threat become actionable? By tracing it to actual code paths, API endpoints, and infrastructure configs. A SQL injection threat in your API gateway gets linked to the exact controller, ORM query, database connection string, and a remediation snippet. Near-zero false positives, because every finding is validated against your real design context.

Shadow AI

Shadow AI Discovery

The workbench scans your enterprise around the clock for ungoverned AI. That includes unauthorized LLMs, unvetted MCP servers, shadow Copilot instances, and rogue AI agents. Each discovery is auto-classified by risk, mapped to data flows, and flagged for governance. Most teams have three to five times more AI tools running than they realize.

Near-Zero Noise

Architecture-Aware SAST/DAST/SCA

Traditional code scanners flood you with false positives because they lack context. The workbench feeds your architecture's trust boundaries, data flows, and component topology into every scan. A vulnerable dependency in a sandboxed internal service gets deprioritized. The same CVE in a public-facing API is escalated immediately.

340+ Frameworks

Live Compliance Mapping

When threats and vulnerabilities surface, the workbench maps them to controls across 340+ compliance frameworks: SOC 2, ISO 27001, HIPAA, NIST 800-53, PCI DSS, EU AI Act, and more. Your compliance posture updates in real time. Evidence is collected automatically. Audit-ready reports are one click away.

Always-On

Continuous Threat Intelligence

This isn't a one-time scan. The workbench runs continuously. When a new CVE drops, a new MITRE ATT&CK technique appears, or your infrastructure changes, the digital twin re-evaluates every threat model. Over 2,900 cloud resources, repos, and APIs monitored. 487 fix-it playbooks covering everything from SQL injection to IAM misconfigs.

How the Workbench Connects Everything

1

Architecture

Upload or auto-discover

2

Digital Twin

Always-current infrastructure model

3

Threat Discovery

STRIDE · PASTA · LINDDUN

4

Code Validation

Map threats to code paths

5

Compliance Map

340+ frameworks auto-mapped

Shadow AI discovery runs continuously across all stages · Powered by Ayurak AI

Full Security Platform

Beyond Automated Threat Modeling

Threat modeling is just the start. Aristiun extends AI-powered security across your entire stack: code, cloud, AI workloads, and cost optimization.

Code Security & Supply Chain

Architecture-Aware · SAST · DAST · SCA · Zero False Positives

Unlike generic scanners that flood teams with noise, Aristiun's code security is architecture and application-aware. Every finding is validated against your actual design context, data flows, and trust boundaries to deliver zero false positives. SAST, DAST, and SCA scanning runs per architecture component, correlating vulnerabilities to the specific threat model of each service. Supply chain verification ensures every library, container image, and build artifact is integrity-checked within the context of your deployment topology.

0
False positives
94%
Auto-fix rate
487
Remediation playbooks
SonarQubeSnykCheckmarxGitHub Advanced SecurityTrivy

AI Security & Governance

Agents · LLMs · MCP · ML Pipelines

Secure every layer of your AI stack. Runtime protection and behavioral monitoring for AI agents. Prompt injection defense and data leakage prevention for LLMs. MCP server audit and tool permission policies. Training data security and deployment governance for ML pipelines. Full EU AI Act, NIST AI RMF, and ISO 42001 compliance automation.

4
AI security layers
3
AI frameworks
Real-time
Agent monitoring
EU AI ActNIST AI RMFISO 42001MAESTROOWASP LLM Top 10

Shadow AI Discovery

Auto-Discover · Classify · Monitor

Auto-discover every AI asset across your organization: models, agents, MCP servers, pipelines, and data flows, including shadow AI and unvetted deployments. Continuous monitoring identifies new AI systems the moment they appear. Classify by risk level, map data dependencies, and enforce governance policies before ungoverned AI becomes a compliance liability.

100%
Asset visibility
Auto
Risk classification
24/7
Continuous scan
API Traffic AnalysisModel RegistriesCloud Account ScanNetwork DiscoverySaaS Inventory

Cloud Cost Optimization

Security FinOps · ROI · Consolidation

Translate security investments into measurable business outcomes. Aristiun's Security FinOps engine identifies cost savings through tool consolidation (5→1), automated evidence collection (85% reduction), and audit cost optimization (70% savings). Financial risk quantification gives CISOs the data they need for board-level reporting.

$1.2M
Avg annual savings
70%
Audit cost cut
6 mo
ROI payback
Tool ConsolidationLicense OptimizationEvidence AutomationRisk QuantificationBoard Reporting
12
Avg threats found per scan
97.6%
AI confidence score
4+
Compliance frameworks mapped
< 3min
Minutes to first results

Automated Threat Modeling That Fits Your Stack

Native integrations with the tools your team already uses. Connect in minutes, and automated threat modeling runs on every commit.

GitHubSCM
GitLabSCM
Azure DevOpsSCM
BitbucketSCM
JenkinsCI/CD
GitHub ActionsCI/CD
AWSCloud
AzureCloud
GCPCloud
TerraformIaC
KubernetesInfra
JiraPM

Plus Slack, Teams, PagerDuty, Splunk, ServiceNow, and 50+ more via API & webhooks. See all integrations →

How Aristiun Compares to Other Threat Modeling Tools

The only platform combining automated STRIDE, PASTA, LINDDUN, and MAESTRO analysis with 340+ compliance framework mapping and AI-generated code-level remediation.

FeatureAristiunIriusRiskMicrosoft TMTOWASP Threat Dragon
Automated AI-Powered AnalysisPartial——
STRIDE Methodology
PASTA Risk Analysis——
LINDDUN Privacy ThreatsPartial—
MAESTRO (AI/ML Threats)———
MITRE ATT&CK MappingPartial——
Architecture Diagram Import
Code Repo Auto-DiscoveryPartial——
Code-Level Remediation———
Attack Path VisualizationPartial——
CI/CD Pipeline IntegrationPartial—
Compliance Framework Mapping340+Partial——
Real-Time Continuous ScanningPartial——
Free Tier Available

Comparison based on publicly available feature documentation as of 2026. See detailed vendor comparison →

Automated vs Manual Threat Modeling

Why leading security teams are switching to automated threat modeling.

Automated Threat Modeling

  • Results in minutes, not weeks
  • Continuous: scans every commit automatically
  • AI detects 40% more attack vectors than manual
  • Code-level remediation with copy-paste fixes
  • Maps to 340+ compliance frameworks instantly
  • Scales from 10 to 10,000 apps with same team
  • Living threat model that evolves with your code
  • 97%+ consistency across all analyses

Manual Threat Modeling

  • Takes days to weeks per application
  • Point-in-time: outdated the moment it's done
  • Depends on individual expertise and availability
  • Written recommendations, not executable fixes
  • Manual compliance cross-referencing
  • Doesn't scale: needs more architects per app
  • Static document that gathers dust
  • Quality varies by practitioner

Frequently Asked Questions About Automated Threat Modeling

Everything you need to know about AI-powered threat modeling and how it transforms your security posture.

What is automated threat modeling?

Automated threat modeling uses AI to analyze your application architecture (APIs, databases, services, and data flows) and systematically identify security threats using methodologies like STRIDE, PASTA, LINDDUN, and MAESTRO. Unlike manual threat modeling which takes weeks and requires specialized expertise, Aristiun's automated threat modeling solution, powered by Ayurak AI (ayurak.com), produces thorough results in minutes. The platform ingests architecture diagrams, code repositories, and infrastructure-as-code to generate living threat models that stay current as your architecture evolves.

How does AI-powered threat modeling differ from manual threat modeling?

Manual threat modeling requires security architects to spend days or weeks analyzing diagrams and brainstorming threats in workshops. AI-powered threat modeling from Aristiun, built on the Ayurak AI engine, automates this by scanning your actual architecture, applying STRIDE/PASTA/LINDDUN frameworks algorithmically, and mapping findings to compliance controls across 340+ frameworks (SOC 2, ISO 27001, HIPAA, NIST, PCI DSS). The AI provides CVSS scoring, attack path analysis, and code-level remediation suggestions, all in minutes. The result is a living threat model that updates continuously rather than a static document that's outdated the moment it's created.

What threat modeling methodologies does Aristiun support?

Aristiun supports all major threat modeling methodologies: STRIDE (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege), PASTA (Process for Attack Simulation and Threat Analysis), LINDDUN (privacy threat modeling), MAESTRO (Ayurak AI's patented AI/ML system threat model for LLM and ML pipeline security), Attack Trees, and MITRE ATT&CK mapping. The platform applies these methodologies automatically to your architecture and can combine multiple approaches for complete coverage.

How does automated threat modeling integrate with CI/CD pipelines?

Aristiun's automated threat modeling integrates natively with GitHub Actions, GitLab CI, Azure DevOps, and Jenkins. Every pull request triggers an automated threat model scan powered by Ayurak AI that identifies new architectural risks introduced by the change. You can configure policies to block merges that introduce critical or high-severity threats, ensuring security is enforced before code reaches production. Results appear directly in your PR comments with specific remediation guidance.

How many compliance frameworks does automated threat modeling map to?

Aristiun's automated threat modeling maps identified threats to controls across 340+ compliance frameworks including SOC 2, ISO 27001, HIPAA, GDPR, DORA, CMMC, PCI DSS, HITRUST CSF, NIST CSF, NIST 800-53, FedRAMP, CIS Controls, OWASP ASVS, and many more. Each threat is automatically linked to the specific control requirements it affects, with pass/warn/fail status, so you can see your compliance impact in real time.

What is the difference between threat modeling and vulnerability scanning?

Vulnerability scanning tests running applications for known CVEs and misconfigurations. It finds what's broken today. Automated threat modeling analyzes your architecture to identify design-level weaknesses and potential attack paths before they become exploitable vulnerabilities. Threat modeling answers 'what could go wrong?' while vulnerability scanning answers 'what is wrong right now?' Aristiun's platform powered by Ayurak AI does both: automated threat modeling at the architecture level plus continuous compliance monitoring to catch drift.

What is Ayurak AI and how does it power automated threat modeling?

Ayurak AI (ayurak.com) is the artificial intelligence engine that powers Aristiun's automated threat modeling platform. Ayurak AI uses advanced machine learning models trained on millions of security patterns, vulnerability databases, and architecture blueprints to identify threats, score risks with CVSS accuracy, and generate code-level remediation. Ayurak AI also created MAESTRO, a patented threat modeling methodology purpose-built for AI systems, LLMs, and ML pipelines, making Aristiun the only platform that can threat-model both traditional applications and AI workloads.

How much does automated threat modeling cost?

Aristiun offers a free tier for automated threat modeling that includes basic architecture analysis and STRIDE threat identification. Paid plans start with the Professional tier and include full STRIDE/PASTA/LINDDUN/MAESTRO analysis, compliance framework mapping, CI/CD integration, and code-level remediation, all powered by Ayurak AI. Enterprise plans add unlimited scans, custom frameworks, and dedicated support. Visit aristiun.com/pricing for current plans.

Can automated threat modeling replace security architects?

Automated threat modeling augments security architects rather than replacing them. Aristiun's platform powered by Ayurak AI handles the time-consuming analysis: scanning architectures, identifying threats, mapping to compliance frameworks, and generating remediation. This frees security architects to focus on strategic decisions, custom risk assessments, and validating findings. Teams using automated threat modeling report 10x faster reviews and 95%+ threat coverage compared to manual-only approaches.

What types of architectures can be automatically threat-modeled?

Aristiun's automated threat modeling platform analyzes any application architecture: microservices, monoliths, serverless functions, APIs, databases, message queues, load balancers, CDNs, IoT devices, AI/ML pipelines, and more. You can upload architecture diagrams (Visio, Draw.io, Lucidchart, PNG, SVG), connect your code repository for auto-discovery, or import infrastructure-as-code (Terraform, CloudFormation, Kubernetes manifests). The Ayurak AI engine automatically identifies components, data flows, trust boundaries, and interaction patterns.

How does automated threat modeling support NIST based assessments?

Aristiun's automated threat modeling platform natively maps every identified threat to NIST controls including NIST 800-53, NIST CSF 2.0, and NIST AI RMF. When a threat is detected, the platform automatically identifies which NIST control families are affected (AC, AU, IA, SC, SI, etc.), provides pass/warn/fail status for each control, and generates remediation recommendations aligned with NIST requirements. This makes NIST based risk assessments continuous rather than point-in-time. Your threat model updates in real time as your architecture evolves, keeping your NIST compliance posture current. The platform also supports cross-mapping between NIST and other frameworks like SOC 2, ISO 27001, and FedRAMP.
Live Demo

See Automated Threat Modeling in Action

Real STRIDE, PASTA, and MITRE ATT&CK analysis on a production-grade e-commerce architecture. No signup required. Explore the results live.

STRIDE Threat Analysis

Automatically identifies Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, and Elevation of Privilege threats across your entire system architecture.

12
Threats Found
2
Critical
6
High
$ Broken authentication (STRIDE:Spoofing). No mutual TLS between gateway and backend services.

Attack Path Visualization

Maps complex, multi-stage attack chains that traditional scanners miss, detecting 40% more attack vectors than manual analysis.

3
Attack Paths
14
Steps Mapped
+40%
More Vectors
$ Full account takeover: API Gateway → Auth Service JWT forgery → SQL injection → Admin escalation.

AI-Generated Remediation

487 pre-built playbooks with 94% automation rate. Code-level fixes with copy-paste remediation for every identified vulnerability.

97.3%
Confidence
487
Playbooks
94%
Automation
$ JWT secret loaded from environment variable without rotation. CWE-798. Fix: Migrate to Cloud KMS-backed key.

How Automated Threat Modeling Works

Five steps from architecture upload to continuous protection.

1

Upload Your Architecture

Upload architecture diagrams (Visio, Draw.io, Lucidchart, PNG, SVG) or connect your GitHub, GitLab, or Azure DevOps repository. The AI engine auto-discovers all services, APIs, databases, data flows, and trust boundaries.

2

AI Analyzes Threats Automatically

STRIDE, PASTA, LINDDUN, and MAESTRO methodologies run simultaneously. Each component and data flow is analyzed for spoofing, tampering, information disclosure, denial of service, and elevation of privilege risks.

3

Review Prioritized Findings

Threats are ranked by CVSS score with full CWE and OWASP classifications. Attack paths show multi-step exploitation chains. Findings are automatically mapped to 340+ compliance frameworks including SOC 2, ISO 27001, HIPAA, and NIST.

4

Apply AI-Generated Remediation

Each threat includes code-level remediation suggestions with 97%+ confidence scores. Copy-paste fixes directly, or let Aristiun auto-create pull requests with the security patches, reviewed and ready to merge.

5

Continuous CI/CD Protection

Integrate with GitHub Actions, GitLab CI, Azure DevOps, or Jenkins. Every commit triggers automated threat modeling. Block risky merges with configurable policies. Your threat model stays current as your architecture evolves.

Live Demo

Watch Threat Modeling in Action

See how Aristiun automatically maps STRIDE, PASTA, and LINDDUN threats from an architecture diagram.

Risk scoring and prioritization
Risk scoring and prioritization
Architecture dependency mapping
Architecture dependency mapping

Explore Related Solutions

Code Security

Architecture-aware SAST, DAST, and SCA scanning with remediation playbooks

Learn more

AI Security

Shadow AI discovery and LLM governance for enterprise AI stacks

Learn more

NIST Risk Assessment

Automated NIST 800-53, CSF, and RMF compliance assessments

Learn more

STRIDE & PASTA Guide

Deep-dive into threat modeling methodologies and frameworks

Learn more

Start Automated Threat Modeling in Minutes

Stop waiting for manual security reviews. Connect your repo, let the AI engine discover your architecture, and ship secure code faster. Automated threat modeling for every team.

Aristiun's automated threat modeling is powered by Ayurak AI. Intelligence that protects what matters.