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Proficient AI — agentic threat model

7.6AIVSS 7.6 · High

Proficient AI is a closed-source SDK and API framework for building conversational agents, presenting risks primarily associated with framework-level vulnerabilities, insecure tool integration, and the inherent opacity of closed-source orchestration.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 6.3AARS uplift 1.26Factor sum 3.4/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.30
Goal-Driven Planning
0.30
Self-Modification
0.10
Dynamic Tool Use
0.40
Persistent Memory
0.40
Contextual Awareness
0.50
Dynamic Identity
0.10
Multi-Agent Interactions
0.20
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 listing describes an SDK/API framework and does not specify the underlying foundation models used, leaving threats like model-specific vulnerabilities or data poisoning unverified.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — The directory listing does not detail how data operations, vector databases, or RAG pipelines are structured or secured within the SDK.

L3 · Agent Frameworks✓ mapped

As a closed-source framework for building and operating conversational agents, vulnerabilities in the SDK orchestration code, insecure tool integration patterns, and conversational memory poisoning represent primary threats.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — While the SDK allows developers to 'deploy and operate' agents, the specific hosting environments, sandboxing capabilities, and secrets management practices are not disclosed.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — There is no mention of built-in evaluation, observability, logging, or guardrail mechanisms within the SDK to detect drift or anomalous agent behavior.

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

Not certain from the listing — No specific security certifications (e.g., SOC2, ISO), compliance alignments, or identity and access management (IAM) controls are detailed in the public listing.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — The framework focuses on conversational agents within apps, but it is unclear if it supports multi-agent ecosystems, agent-to-agent trust boundaries, or marketplace integrations.

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.