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rzndtra-x402 — agentic threat model

7.9AIVSS 7.9 · High

rzndtra-x402 acts as a critical financial and intelligence hub for the agentic economy, making its compromise highly impactful due to cascading A2A risks. Its keyless, wallet-only authentication model and dynamic tool routing (e.g., code review, scraping) present unique security and compliance challenges.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 0.79Factor sum 5.0/10Threat ×1.05Mitigation ×0.85
Autonomy of Action
0.40
Goal-Driven Planning
0.30
Self-Modification
0.10
Dynamic Tool Use
0.70
Persistent Memory
0.60
Contextual Awareness
0.50
Dynamic Identity
0.40
Multi-Agent Interactions
0.90
Non-Determinism
0.50
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 platform routes to 15+ endpoints and LLM inference routing but does not disclose the specific underlying foundation models used, making them susceptible to model routing manipulation or upstream model poisoning.

L2 · Data Operations✓ mapped

The platform aggregates and processes transaction data, wallet profiles, and behavioral analytics. Threats include data poisoning of the intelligence feed (e.g., wash trading to skew popularity indexes) and potential privacy leaks of agent wallet profiles.

L3 · Agent Frameworks✓ mapped

Integrates directly via OpenAPI specs and A2A protocols. Risks include insecure tool integration where external agents invoke endpoints (like web scraping or code review) to execute malicious payloads or exploit injection vulnerabilities in the routing logic.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — while it operates on Base and Solana blockchains for pay-per-call transactions, the hosting, sandboxing of scraping/code review tools, and secret management for blockchain nodes are not detailed.

L5 · Evaluation & Observability✓ mapped

Features active wash detection, risk scoring, and real-time uptime monitoring. However, gaps may exist in detecting sophisticated adversarial prompt injections or evasion of the wash detection algorithms.

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

The 'no API keys, no accounts' model relies entirely on blockchain-based identity (wallets). This introduces compliance risks (e.g., AML/KYC gaps) and security risks if a wallet is compromised, as there is no traditional access control.

L7 · Agent Ecosystem✓ mapped

Highly exposed to ecosystem risks. It serves as a central hub for multi-agent transactions. A compromise could lead to cascading failures across dependent agents, trust abuse via manipulated popularity indexes, or economic exploits.

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.