What is automated threat modeling?

Automated threat modeling uses AI to identify, classify, and prioritize security threats across your infrastructure and applications. Aristiun's Unified Threat Workbench powered by Ayurak AI lets you upload diagrams, collaborate in real time, and generate secure architectures with AI copilots. It automates STRIDE, PASTA, LINDDUN, and MAESTRO methodologies to continuously map your threat landscape against 340+ compliance frameworks.

Modern GRC (Governance, Risk, and Compliance) replaces legacy spreadsheet-based compliance with AI-powered automation. Aristiun's modern GRC platform provides real-time compliance scoring, automated evidence collection, cross-framework control mapping, and continuous monitoring across 340+ standards including SOC 2, ISO 27001, HIPAA, GDPR, and DORA.

How does Aristiun handle AI Governance and EU AI Act compliance?

Aristiun provides comprehensive AI governance covering the EU AI Act, NIST AI RMF, ISO 42001, and ISO 23894. The platform automates AI risk classification, model inventory management, bias monitoring, transparency reporting, and evidence collection to ensure your AI systems comply with global AI regulations.

How many compliance frameworks does Aristiun support?

Aristiun supports 340+ security and compliance frameworks including SOC 2, ISO 27001, HIPAA, GDPR, DORA, CMMC, PCI DSS, HITRUST CSF, NIST CSF, NIST 800-53, FedRAMP, CIS Controls, CCPA, EU AI Act, ISO 42001, and many more. The platform provides cross-framework control mapping to eliminate duplicate work.

How do you prevent prompt injection attacks?

We use a multi-layer approach. Input sanitization strips malicious instructions before they reach the model. Instruction hierarchy enforcement keeps system prompts from being overridden. Canary tokens detect injection attempts in real time. Output classifiers verify responses haven't been tampered with. This handles both direct injections in user input and indirect injections hidden in external data sources like web pages or documents.

What is shadow AI and why is it dangerous?

Shadow AI is any AI tool or model used in your org without IT or security approval. Here's why that matters: ungoverned AI can process sensitive data without encryption, leak proprietary information to third-party APIs, violate regulatory requirements, and create compliance gaps you don't know about. Aristiun's Shadow AI Discovery scans your environment continuously to find and classify all AI usage.

What is MCP security?

MCP stands for Model Context Protocol. It is how AI agents connect to external tools. MCP security means auditing those servers for vulnerabilities, enforcing tool permission policies, logging every tool invocation, and verifying supply chain integrity. As agents use MCP more to interact with external systems, these connections become a real attack surface for data exfiltration and unauthorized actions.

How does the EU AI Act affect AI security?

If you deploy high-risk AI systems, the EU AI Act requires thorough risk management, transparency, human oversight, technical documentation, and conformity assessments. In practice, Aristiun maps your AI security posture to all 42 EU AI Act controls, automates evidence collection, and runs continuous compliance monitoring so you're not scrambling before an audit.

What is the NIST AI Risk Management Framework?

The NIST AI RMF is a voluntary framework for managing AI risk. It has four core functions: Govern (set AI risk policies), Map (identify and categorize risks), Measure (quantify them), and Manage (treat and monitor). Think of it as a structured way to make sure nothing slips through the cracks. Aristiun provides automated alignment with all 72 NIST AI RMF subcategories.

How do you secure AI agents in production?

You need behavior monitoring to catch anomalous actions, permission boundaries to limit what agents can do, guardrails on inputs and outputs, secure multi-agent communication, and complete audit logging. Aristiun covers all of this in the 4-Layer AI Security Stack, with real-time alerts and automated incident response.

What is AI supply chain security?

It protects the components that make up your AI systems: model weights, training data, tool packages, MCP servers, and dependencies. Supply chain attacks can introduce backdoors in models, poison training data, or compromise tool integrations. Aristiun verifies integrity with cryptographic signing, dependency scanning, and provenance tracking across the full AI supply chain.

AI Security Platform

AI & LLM Security Platform

Secure AI agents, LLMs, MCP integrations, and ML pipelines. Discover shadow AI. Prevent prompt injection. Ensure AI compliance.

4-Layer AI Security Stack

Shadow AI Discovery

EU AI Act Ready

NIST AI RMF Compliant

Defense in Depth

The 4-Layer AI Security Stack

Protection across every layer of your AI infrastructure, from agents and LLMs to MCP integrations and ML pipelines.

Behavior Monitoring

Real-time tracking of agent actions, tool calls, and decision patterns to detect anomalous behavior.

Permission Boundaries

Fine-grained permission policies that limit what each agent can access, execute, and modify.

Guardrails

Input/output guardrails that enforce safety constraints and prevent harmful or off-policy responses.

Multi-Agent Orchestration Security

Secure communication channels between agents with trust verification and delegation controls.

Major Differentiator

Shadow AI Discovery

Auto-discover ungoverned AI across your enterprise. Employees use dozens of AI tools without security team visibility. Aristiun finds most of them, classifies the risk, and enforces your policies.

Continuous Discovery

Automatically detect AI tools, APIs, and models being used across your organization, including unsanctioned deployments.

Risk Classification

Classify discovered AI by risk level based on data access, model capabilities, deployment context, and regulatory exposure.

Usage Analytics

Full visibility into who is using which AI, how often, with what data, and for what purpose.

Policy Enforcement

Enforce organizational AI policies automatically. Block unapproved models, require approval workflows, and alert on violations.

Average enterprise discovers 47 ungoverned AI tools in the first scan

Compliance Automation

AI Compliance Frameworks

Map your AI security posture to the world's leading AI governance frameworks. Automated evidence collection and continuous compliance monitoring.

EU AI Act

42 controls

Full compliance mapping for high-risk AI systems including risk assessment, transparency obligations, and human oversight requirements.

NIST AI RMF

72 subcategories

Map, Measure, Manage, and Govern. Full alignment with the NIST AI Risk Management Framework core functions.

ISO 42001

38 controls

AI management system certification support with automated evidence collection and continuous compliance monitoring.

OWASP Top 10 for LLMs

10 risk categories

Protection against all OWASP LLM risks including prompt injection, insecure output handling, and model theft.

Threat Prevention

Prompt Injection & AI Attack Prevention

Understand the attack vectors targeting your AI systems and how Aristiun prevents each one with layered defenses.

Direct Prompt Injection

Malicious instructions embedded directly in user input to override system prompts and safety guidelines.

Prevention

Multi-layer input sanitization, instruction hierarchy enforcement, and canary token detection.

Indirect Prompt Injection

Hidden instructions in external data sources (web pages, documents, emails) that get processed by the LLM.

Prevention

Data source isolation, content scanning before ingestion, and instruction-data separation boundaries.

Jailbreaking

Techniques to bypass model safety training using role-play, encoding tricks, or multi-turn conversation manipulation.

Prevention

Output classifiers, behavioral pattern detection, and dynamic guardrail adaptation.

Data Extraction

Probing the model to extract training data, system prompts, API keys, or other sensitive information.

Prevention

Output filtering, membership inference detection, and differential privacy enforcement.

Model Manipulation

Adversarial inputs designed to produce incorrect predictions, bypass classifiers, or cause model misbehavior.

Prevention

Adversarial input detection, ensemble verification, and confidence threshold enforcement.

AI Supply Chain Attack

Compromised model weights, poisoned fine-tuning data, or malicious tool packages in the AI development pipeline.

Prevention

Cryptographic model signing, dependency scanning, and provenance verification across the supply chain.

Real-Time Visibility

AI Risk Dashboard

Complete visibility into your AI security posture. Monitor every model, agent, and tool across your enterprise from one dashboard.

Model Inventory

Complete catalog of all AI models in use, both approved and shadow. Track model versions, owners, and deployment locations.

Risk Scores

Dynamic risk scoring for every AI asset based on vulnerability exposure, data sensitivity, and compliance gaps.

Compliance Status

Real-time compliance posture across EU AI Act, NIST AI RMF, ISO 42001, and OWASP Top 10 for LLMs.

Usage Metrics

Token consumption, API call volumes, user adoption rates, and cost analytics across all AI deployments.

Ecosystem

Integrates With Your AI Stack

Native integrations with the leading AI platforms, frameworks, and orchestration tools.

OpenAI

Anthropic

Google AI

Azure AI

AWS Bedrock

Hugging Face

LangChain

CrewAI

AutoGen

Knowledge Base

Frequently Asked Questions

Everything you need to know about AI security, prompt injection prevention, and AI compliance.

AI security covers the practices, tools, and policies that protect AI systems, including LLMs, agents, and ML pipelines, from adversarial attacks, data breaches, and misuse. It spans the entire AI lifecycle: training data security, inference monitoring, prompt injection prevention, model access controls, output filtering, and compliance with regulations like the EU AI Act and NIST AI RMF.

AI Security Inside the Unified Workbench

AI security is built into Aristiun's unified workbench alongside your digital twin, threat models, and compliance posture. Discover shadow AI, validate AI-specific threats against actual agent code and MCP configurations, and auto-map findings to EU AI Act, NIST AI RMF, and ISO 42001 controls. All from one workspace.

Digital Twin + AI InventoryAgent Code ValidationShadow AI DiscoveryMCP Server AuditAI Compliance Mapping

Live Demo

AI Security Platform Demo

Discover shadow AI, classify model risks, and enforce governance policies across your organization.

AI/ML security review dashboard

Full AI model visibility

Secure Your AI Stack Today

Don't wait for an AI security incident. Get complete visibility and control over your AI agents, LLMs, MCP tools, and ML pipelines. Start protecting your enterprise AI in minutes.

Aristiun's AI security platform is powered by Ayurak AI — intelligence that protects what matters.

AI & LLM Security Platform

The 4-Layer AI Security Stack

Behavior Monitoring

Permission Boundaries

Guardrails

Multi-Agent Orchestration Security

Shadow AI Discovery

Continuous Discovery

Risk Classification

Usage Analytics

Policy Enforcement

AI Compliance Frameworks

EU AI Act

NIST AI RMF

ISO 42001

OWASP Top 10 for LLMs

Prompt Injection & AI Attack Prevention

Direct Prompt Injection

Indirect Prompt Injection

Jailbreaking

Data Extraction

Model Manipulation

AI Supply Chain Attack

AI Risk Dashboard

Model Inventory

Risk Scores

Compliance Status

Usage Metrics

Integrates With Your AI Stack

Frequently Asked Questions

AI Security Inside the Unified Workbench

AI Security Platform Demo

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