What ARIA assesses
ARIA combines offensive security validation, AI risk review, threat modeling, and governance evidence into one controlled workflow.
Application and API security
Assess authentication, authorization, tenant isolation, data exposure, business logic, unsafe integrations, input handling, and release risk.
Cloud and identity posture
Review identity boundaries, secrets handling, exposed services, privilege assumptions, lateral movement paths, and cloud control gaps.
LLM, RAG, and MCP testing
Check prompt injection, sensitive information disclosure, retrieval poisoning, excessive agency, insecure tool calls, memory risks, and output handling.
Multi-agent security swarm
Coordinate specialized agents for scoping, surface mapping, cyber review, LLM risk review, threat modeling, governance checks, reporting, and peer review.
Threat model paths
Build paths across assets, users, trust boundaries, attacker-controlled inputs, data movement, controls, detections, and residual risk.
Governance evidence
Map findings and controls to OWASP LLM and agentic AI risk areas, AI Verify-style principles, and internal approval requirements.
ARIA module map
Use the buttons to see what each public capability means inside ARIA.
Web and API assessment
ARIA turns an authorized application or API scope into a test plan for authentication, authorization, tenant separation, data exposure, business logic, unsafe integrations, and release-specific change risk. Output: mapped surfaces, observations, validation tasks, remediation notes, and retest items.
Validation loop
ARIA is built around repeatable validation rather than one-off static notes.
Traditional cycle
Point-in-time security work
Scoping, testing, report delivery, remediation, and retest often happen as separate events. Context is easy to lose, and the posture may already have changed by the time a report is acted on.
ARIA cycle
Find, validate, fix, retest
ARIA keeps scope, observations, agent activity, evidence, remediation tasks, and retest criteria together so the same assessment can evolve with product and AI-system change.
AI swarm roles
ARIA shows what the agents are doing so the workflow stays reviewable.
Intake controller
Confirms scope, authorization, constraints, and required output type before assessment work begins.
Surface mapper
Builds the map of assets, roles, data movement, trust boundaries, tools, and model interfaces.
Cyber tester
Reviews application, API, identity, cloud, secrets, and business-logic risk against the approved scope.
LLM tester
Checks LLM, RAG, MCP, agent-tool, prompt, memory, and data-leakage failure modes.
Threat modeller
Chains observations into threat paths with controls, detection ideas, and residual risk.
Governance reviewer
Maps evidence to AI Verify-style principles, OWASP risk areas, and internal approval needs.
Evidence reporter
Turns agent activity into a concise record of observations, assumptions, gaps, fixes, and retest tasks.
Human approver
Keeps high-impact conclusions, escalation, and access decisions under accountable human control.
Framework-informed paths
OWASP LLM and GenAI risks
ARIA supports prompt injection, sensitive information disclosure, supply-chain risk, data and model poisoning, excessive agency, system prompt leakage, vector and embedding weaknesses, misinformation, insecure output handling, and unbounded consumption review paths.
OWASP agentic AI risk areas
ARIA treats agent skills, tool permissions, repository or workflow instructions, memory, external actions, and approval gates as security-relevant execution surfaces.
AI Verify-style governance
ARIA tracks transparency, explainability, reproducibility, safety, security, robustness, fairness, data governance, accountability, human agency, and broader societal considerations as evidence categories.
Cybersecurity and cloud posture
ARIA organizes application, API, identity, cloud, secrets, CI/CD, and workflow risks into a defensive assessment plan suitable for security teams.
Threat modeling
ARIA builds paths across assets, trust boundaries, attacker-controlled inputs, data movement, AI abuse cases, controls, detections, and residual risk.
Continuous exposure management
ARIA helps move from discovery and prioritization to validation, remediation, and retest records that can be refreshed when the system changes.
Evidence model
ARIA reports are meant to be useful to engineers, security leads, and governance reviewers.
Access and operating model
Public pages explain capabilities. Sensitive platform state stays behind authentication.
Role-based views
Platform administratorSecurity leadAssessment operatorRead-only viewer
Each category gets different views and permitted actions inside the authenticated workspace.
Tenant separation
Users are separated by their organization identity so one customer cannot view another customer workspace, observables, assessments, or outputs.
Operational privacy
Deployment parameters, assessment targets, model configuration, customer data, credentials, and tenant records are not published on the public site.