agntk — agentic threat model
agntk presents a high-risk profile due to its local execution model, persistent named agents, and 20+ built-in tools running directly on host hardware, which can lead to host compromise if malicious prompts are processed.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.30 | |
| Dynamic Tool Use | 0.90 | |
| Persistent Memory | 0.80 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.40 | |
| 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.
Utilizes local models with hardware-aware selection. Threats include model reprogramming and adversarial prompt injection that can bypass local safety alignments, especially when executing local CLI commands.
Not certain from the listing — likely interacts with local files and codebase context as a Claude Code plugin. Gaps in data lineage or lack of input sanitization could allow local data exfiltration or poisoning of the agent's context.
Features persistent named agents and 20+ built-in tools. High risk of tool misuse, insecure tool integration, and prompt injection leading to arbitrary local command execution via the CLI framework.
Runs locally as a CLI tool/plugin. Lacks built-in sandboxing or containerization by default, making host compromise, privilege escalation, and lateral movement highly plausible if the agent is compromised.
Not certain from the listing — no explicit mention of local logging, guardrails, or evaluation frameworks to detect anomalous tool execution or malicious command drift.
Being an open-source, zero-config local CLI tool, it lacks centralized identity, authorization policies, or audit trails, relying entirely on the host user's operating system permissions.
Operates as a Claude Code plugin/toolkit. Risks include cascading failures or trust abuse if integrated with other upstream developer agents or external package ecosystems.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).