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Flowhunt — agentic threat model

9.2AIVSS 9.2 · Critical

Flowhunt presents a moderate-to-high agentic risk due to its extensive third-party integrations (Shopify, HubSpot, Slack) and RAG capabilities, which could be exploited via indirect prompt injection to perform unauthorized actions in connected business systems.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 0.72Factor sum 4.8/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.60
Goal-Driven Planning
0.50
Self-Modification
0.10
Dynamic Tool Use
0.70
Persistent Memory
0.40
Contextual Awareness
0.80
Dynamic Identity
0.30
Multi-Agent Interactions
0.40
Non-Determinism
0.60
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 external foundation models (e.g., OpenAI, Anthropic) integrated via API, exposing it to prompt injection, model misalignment, and API-based data leakage.

L2 · Data Operations✓ mapped

Supports knowledge source integration (databases, websites) for RAG, making it highly vulnerable to data poisoning, indirect prompt injection via scraped websites, and unauthorized data exfiltration.

L3 · Agent Frameworks✓ mapped

Orchestrates workflows via a visual flow builder with task decomposition and query expansion. Risks include insecure tool integration, logic flaws in custom workflows, and tool misuse.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — as a closed-source SaaS platform, infrastructure security, sandboxing of execution environments, and secrets management for third-party integrations are opaque.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — lacks explicit mention of built-in guardrails, evaluation frameworks, or observability logging, creating potential blind spots for drift and anomalous agent behavior.

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

Not certain from the listing — handles sensitive integrations (HubSpot, Shopify) but does not detail access controls, encryption, or compliance certifications (e.g., SOC2, GDPR).

L7 · Agent Ecosystem✓ mapped

Integrates with external ecosystems (Shopify, HubSpot, Slack), creating risks of cascading failures, unauthorized actions in connected platforms, and API trust abuse.

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