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PaidAI — agentic threat model

9.0AIVSS 9.0 · Critical

PaidAI acts as a financial orchestration and billing layer for AI agents, presenting high transactional and financial risks if compromised, despite having low autonomous planning capabilities.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 0.48Factor sum 3.2/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.60
Goal-Driven Planning
0.20
Self-Modification
0.00
Dynamic Tool Use
0.40
Persistent Memory
0.50
Contextual Awareness
0.30
Dynamic Identity
0.20
Multi-Agent Interactions
0.50
Non-Determinism
0.20
Opacity & Reflexivity
0.30

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 supports multiple AI models for tracking and billing, but the specific foundation models used internally and their vulnerability to prompt injection or alignment issues are not disclosed.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — It tracks costs and usage data for AI agent workflows, but the storage mechanisms, data lineage, and protection against data exfiltration of sensitive financial metrics are unspecified.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — The orchestration framework managing the automated pricing and subscription logic is not detailed, leaving potential risks around insecure tool integration for payment gateways unverified.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — The hosting infrastructure, secrets management for API integrations, and network sandboxing are not described in the public directory.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — While the platform provides executive reporting for ROI and cost tracking, the internal guardrails, anomaly detection for billing discrepancies, and security logging are not detailed.

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

Not certain from the listing — Despite handling sensitive billing, subscription, and payment data, the listing does not explicitly cite compliance certifications such as PCI-DSS, SOC2, or specific identity and access management controls.

L7 · Agent Ecosystem✓ mapped

PaidAI is deeply integrated into the agent ecosystem, tracking costs and billing for other AI agents' actions. This creates a high risk of cascading failures or financial exploitation if downstream agents are compromised and manipulate their reported activity.

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.