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Cleo — agentic threat model

8.3AIVSS 8.3 · High

Cleo presents a moderate-to-high risk profile due to its integration of automated web scraping (susceptible to indirect prompt injection from competitor sites) and a cryptocurrency payment system, which introduces direct financial vectors if compromised.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 7.5AARS uplift 0.8Factor sum 3.2/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.50
Goal-Driven Planning
0.40
Self-Modification
0.00
Dynamic Tool Use
0.60
Persistent Memory
0.20
Contextual Awareness
0.50
Dynamic Identity
0.10
Multi-Agent Interactions
0.00
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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — likely relies on third-party LLMs for text synthesis. The primary threat is indirect prompt injection, where malicious instructions embedded in competitor websites could hijack the model's analysis or output generation.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — ingests real-time external web data for competitive intelligence. This exposes the agent to data poisoning or manipulation if competitors publish deceptive content specifically designed to mislead automated scrapers.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — orchestrates scraping tools and a cryptocurrency payment API. Insecure tool integration could allow a manipulated LLM context to trigger unauthorized crypto transactions or alter payment destinations.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — web-hosted deployment. The scraping infrastructure requires strict sandboxing and network segmentation to prevent Server-Side Request Forgery (SSRF) when fetching untrusted competitor URLs.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — no observability or guardrail mechanisms are mentioned. Without real-time monitoring, prompt injection attacks or scraping failures may go unnoticed, leading to corrupted intelligence reports.

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

Not certain from the listing — the integration of cryptocurrency payments introduces significant compliance, KYC/AML, and financial security challenges that are not detailed in the public directory.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — operates as a standalone web agent. However, it interacts with external blockchain ecosystems for payments, introducing risks related to smart contract vulnerabilities or transaction intercept attacks.

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