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lowtouch.ai — agentic threat model

8.9AIVSS 8.9 · High

lowtouch.ai acts as an enterprise-grade no-code agent platform connecting directly to internal apps and APIs, presenting significant risk of unauthorized tool execution and privilege escalation if agent orchestration or API integrations are compromised.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 0.84Factor sum 5.6/10Threat ×1.0Mitigation ×0.95
Autonomy of Action
0.80
Goal-Driven Planning
0.70
Self-Modification
0.20
Dynamic Tool Use
0.80
Persistent Memory
0.50
Contextual Awareness
0.60
Dynamic Identity
0.60
Multi-Agent Interactions
0.30
Non-Determinism
0.60
Opacity & Reflexivity
0.50

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 specific foundation models utilized by lowtouch.ai are not disclosed, leaving potential vulnerabilities to model-specific prompt injection or adversarial exploitation unverified.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — While the platform emphasizes that enterprises maintain complete control over their data, the specific mechanisms for data operations, vector storage, and RAG security are not detailed.

L3 · Agent Frameworks✓ mapped

As a platform designed to turn existing apps and APIs into task-driven agents, L3 risks are highly critical. Insecure tool integration, unauthorized API execution, and flawed orchestration logic represent primary attack vectors if agent planning is manipulated.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — The platform states agents operate within the enterprise's own infrastructure, but details regarding containerization, network isolation, and secrets management for API keys are not provided.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — There is no mention of built-in evaluation frameworks, real-time guardrails, or observability logging to detect anomalous agent behavior or drift.

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

Not certain from the listing — Although marketed as secure and allowing enterprises to maintain control, specific compliance alignments (e.g., SOC2, ISO 27001) or granular role-based access controls (RBAC) are not explicitly detailed.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — The platform supports deploying multiple intelligent agents, but whether these agents interact in a multi-agent ecosystem or marketplace with cascading trust risks is not specified.

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