Origin Protocol — agentic threat model
Origin Protocol acts as a critical trust and transactional layer for autonomous agents on the Base blockchain, introducing significant financial and multi-agent systemic risks if its identity or reputation systems are compromised.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.60 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.90 | |
| Multi-Agent Interactions | 1.00 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.40 |
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 — Origin Protocol is a framework and trust layer rather than a specific foundation model, so model-level vulnerabilities depend on the external LLMs integrated by developers.
Not certain from the listing — while it manages reputation data and trust profiles, the specific data operations, vector stores, or RAG pipelines used to calculate these scores are not detailed.
The framework orchestrates agent-to-agent commerce and integrates payment protocols (x402). Vulnerabilities here include insecure tool integration with blockchain wallets and potential exploitation of payment execution logic.
Built on the Base blockchain network. Infrastructure threats include smart contract vulnerabilities, gas limit exploits, and decentralized node infrastructure compromise.
Not certain from the listing — although it provides a reputation and trust scoring layer for external agents, the internal evaluation, logging, and drift detection of Origin's own scoring algorithms are unspecified.
Strong focus on decentralized identity (DID) and verifiable trust profiles. Security controls center on cryptographic identity verification and reputation-based authorization policies.
Highly exposed to ecosystem risks. Malicious or compromised agents could manipulate the reputation system, execute fraudulent transactions, or trigger cascading financial failures across the agent-to-agent economy.
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.