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Arya-AI — agentic threat model

9.6AIVSS 9.6 · Critical

Arya-AI presents a high agentic risk profile due to its multi-agent architecture executing over 150 tasks across 10 enterprise departments, combined with a lack of explicit security controls in its public listing.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 1.06Factor sum 6.7/10Threat ×1.05Mitigation ×1.0
Autonomy of Action
0.80
Goal-Driven Planning
0.80
Self-Modification
0.30
Dynamic Tool Use
0.80
Persistent Memory
0.50
Contextual Awareness
0.70
Dynamic Identity
0.60
Multi-Agent Interactions
0.90
Non-Determinism
0.60
Opacity & Reflexivity
0.70

Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.

MAESTRO 7-layer threat model

Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — The listing does not specify the underlying foundation models used by Arya-AI. Threats include potential model vulnerabilities, adversarial examples, or misaligned outputs depending on the chosen LLM.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — The listing does not detail how data operations, RAG, or vector databases are managed, though it supports 150+ tasks across 10 departments. Threats include data poisoning or exfiltration of sensitive departmental data.

L3 · Agent Frameworks✓ mapped

Arya-AI integrates multiple AI agents to execute 150+ tasks across 10 departments, indicating a complex orchestration framework. Threats include tool misuse, insecure tool integration, and framework vulnerabilities during task execution.

L4 · Deployment & Infrastructure✓ mapped

Arya-AI offers both cloud and on-premise deployment options. Threats include container/host compromise, privilege escalation, and lateral movement within the enterprise network or cloud environment.

L5 · Evaluation & Observability✓ mapped

Arya-AI features real-time performance and sustainability tracking. Threats include blind spots in logging agentic actions across 150+ tasks or insufficient guardrails to detect anomalous behavior.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — The listing does not mention specific security certifications (like SOC2, ISO) or identity/access management controls, despite offering on-premise deployment.

L7 · Agent Ecosystem✓ mapped

Arya-AI explicitly integrates the capabilities of multiple AI agents into one advanced system to execute tasks. Threats include multi-agent trust abuse, cascading failures across agents, and rogue agent behavior within the internal ecosystem.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).