Fleek — agentic threat model
Fleek is a high-risk agentic platform due to its integration of autonomous AI agents with on-chain blockchain environments, where compromise can lead to direct, irreversible financial and smart contract execution exploits.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.80 | |
| Multi-Agent Interactions | 0.50 | |
| 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.
Not certain from the listing — Fleek is a deployment platform and does not specify which foundation models are supported, though model reprogramming or adversarial exploitation could lead to unauthorized blockchain transactions.
Not certain from the listing — The description focuses on deployment and blockchain integration rather than data ingestion, vector databases, or RAG pipelines.
Fleek provides templates and orchestration for autonomous agents. Threats include insecure tool integration (specifically blockchain/smart contract execution tools) and vulnerabilities within the pre-built templates that could be exploited to hijack agent logic.
As an open-source, auto-scalable cloud hosting platform, key threats include container escape, host compromise, lateral movement within the multi-tenant cloud, and exposure of sensitive deployment secrets or private keys.
Not certain from the listing — There is no explicit mention of evaluation frameworks, real-time monitoring, logging, or guardrails for the deployed autonomous agents.
Not certain from the listing — Although the platform claims to be 'verifiable', specific details regarding identity management, access control policies, and regulatory compliance are not provided.
The platform enables an ecosystem of autonomous agents interacting with on-chain environments. Threats include rogue or compromised agents executing malicious transactions, trust abuse between interacting agents, and cascading failures across decentralized applications.
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.