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Alethea AI — agentic threat model

8.8AIVSS 8.8 · High

Alethea AI presents a unique risk profile centered on decentralized, evolving iNFTs interacting within a multi-agent metaverse, where the primary threats involve smart contract vulnerabilities, state/memory poisoning, and unpredictable emergent behaviors from autonomous digital assets.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 6.5AARS uplift 2.27Factor sum 6.5/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.60
Goal-Driven Planning
0.40
Self-Modification
0.70
Dynamic Tool Use
0.30
Persistent Memory
0.80
Contextual Awareness
0.60
Dynamic Identity
0.80
Multi-Agent Interactions
0.80
Non-Determinism
0.70
Opacity & Reflexivity
0.80

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 — Alethea AI uses underlying generative AI models to power iNFTs, but the specific foundation models, training, or alignment techniques are not disclosed, leaving potential exposure to adversarial prompt injection or model reprogramming.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — Data operations likely involve on-chain metadata and off-chain decentralized storage (e.g., IPFS) to persist iNFT state, risking data/knowledge-base poisoning or metadata manipulation.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — The orchestration framework for iNFT evolution and real-time interaction is proprietary, presenting risks of memory poisoning or state manipulation as the agents 'evolve' over time.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — Deployment spans decentralized nodes and blockchain smart contracts, exposing the system to smart contract vulnerabilities, oracle manipulation, or node compromise rather than traditional cloud hosting risks.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — There is no mention of evaluation, monitoring, or guardrails to prevent iNFTs from generating harmful, offensive, or misaligned outputs during real-time interactions in the metaverse.

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

Not certain from the listing — Security relies heavily on blockchain-level ownership (NFTs), but compliance with AI regulations (e.g., EU AI Act) and traditional identity/access management controls are unspecified.

L7 · Agent Ecosystem✓ mapped

The protocol explicitly supports multi-agent interactions ('interact, evolve') in a decentralized metaverse, creating significant risks of cascading failures, rogue agent interactions, and A2A trust abuse where compromised iNFTs can exploit others.

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