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SUI Agents — agentic threat model

9.6AIVSS 9.6 · Critical

SUI Agents presents a high-risk profile due to its integration of autonomous AI personas with on-chain financial capabilities (tokenization, trading) and social media APIs. The combination of financial agency and public-facing communication channels amplifies the potential impact of prompt injection or agent compromise.

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 6.4/10Threat ×1.1Mitigation ×1.0
Autonomy of Action
0.80
Goal-Driven Planning
0.60
Self-Modification
0.20
Dynamic Tool Use
0.80
Persistent Memory
0.50
Contextual Awareness
0.70
Dynamic Identity
0.80
Multi-Agent Interactions
0.70
Non-Determinism
0.70
Opacity & Reflexivity
0.60

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 specific foundation models powering the zero-code generative infrastructure are not disclosed, leaving potential vulnerabilities to model-specific prompt injection, adversarial reprogramming, or data poisoning unassessed.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — While the platform supports customization and persona creation, details regarding vector databases, RAG pipelines, or training data security are omitted, posing risks of data exfiltration or knowledge-base poisoning.

L3 · Agent Frameworks✓ mapped

The platform serves as an agent creation framework. Key threats include insecure tool integration (specifically blockchain wallet and smart contract interactions) and memory poisoning via community-driven public chats that could manipulate agent behavior.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — The hosting environment for these on-chain digital agents is unspecified. Without details on sandboxing or secure key management for the Sui blockchain wallets, there is a risk of host compromise or private key theft.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — No evaluation frameworks, real-time monitoring, or guardrails are mentioned to detect drift, anomalous trading behavior, or malicious social media outputs generated by the agents.

L6 · Security & Compliance (cross-cutting)✓ mapped

The platform is closed-source and handles tokenized assets on the Sui blockchain. The lack of visible compliance certifications, security audits, or decentralized governance controls increases the risk of regulatory non-compliance and smart contract vulnerabilities.

L7 · Agent Ecosystem✓ mapped

SUI Agents establishes a marketplace/ecosystem for launching and trading agents. This introduces significant risks of cascading financial failures, rogue/compromised agents manipulating token prices, and trust abuse during multi-agent interactions in public chats.

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

These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.