AgentReadyHomeAgent ListingPricing

← LLM Agents

LLM Agents — agentic threat model

8.3AIVSS 8.3 · High

LLM Agents is a minimalistic open-source framework that introduces moderate agentic risk due to its command-and-tool execution loop, which lacks built-in sandboxing or guardrails. The security posture relies heavily on the developer's implementation of downstream controls and secure tool boundaries.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 7.3AARS uplift 1.03Factor sum 3.8/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.60
Goal-Driven Planning
0.50
Self-Modification
0.10
Dynamic Tool Use
0.60
Persistent Memory
0.20
Contextual Awareness
0.40
Dynamic Identity
0.10
Multi-Agent Interactions
0.10
Non-Determinism
0.70
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 framework is model-agnostic, meaning L1 threats like adversarial prompt injection or model misalignment depend entirely on the user-selected foundation model.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — No built-in RAG or vector database integrations are specified in this minimalistic library, leaving data operations and associated poisoning risks to the developer's implementation.

L3 · Agent Frameworks✓ mapped

As a minimalistic library executing a loop of commands and tool integrations, L3 is highly relevant. Vulnerabilities include insecure tool integration, command execution loops without strict validation, and prompt injection leading to unauthorized tool execution.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — The library is open-source and run locally or self-hosted; infrastructure security, sandboxing of tool execution, and secrets management are entirely up to the deploying developer.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — There are no mentioned built-in evaluation, logging, or guardrail mechanisms, creating potential blind spots unless external observability tools are integrated.

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

Not certain from the listing — No built-in authentication, authorization, or compliance controls are mentioned in this minimalistic framework.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — The description does not indicate multi-agent coordination or marketplace features, focusing instead on single-agent command loops.

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.