Arnis — agentic threat model
Arnis is a low-risk, procedural map-generation utility with minimal agentic capabilities, posing virtually no autonomous threat. The primary security risks are limited to traditional web vulnerabilities, such as client-side malicious file generation or server-side denial of service via large OpenStreetMap queries.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.10 | |
| Opacity & Reflexivity | 0.10 |
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.
Not certain from the listing — Arnis appears to be a procedural/algorithmic converter rather than an LLM-based agent, meaning foundation model threats like adversarial reprogramming or prompt injection are likely inapplicable.
Ingests external OpenStreetMap (OSM) data. Threats include data poisoning where malicious or malformed OSM data is used to cause parser errors, application crashes, or generate offensive/unexpected map geometry.
Not certain from the listing — The tool likely uses standard procedural code rather than an AI agent orchestration framework. Risks of tool misuse or autonomous planning vulnerabilities are absent.
Hosted as a browser-based tool. Key threats include server-side resource exhaustion (DoS) if users request extremely large map areas for conversion, and potential vulnerabilities in the ZIP/.mcworld generation libraries.
Not certain from the listing — There is no mention of logging, input validation limits, or observability tools to monitor abuse or anomalous generation requests.
Operates with a 'no signup required' model, meaning there are no identity, authentication, or authorization controls. While this minimizes PII collection, it prevents rate limiting or user-based access policies.
The tool operates as a standalone utility with no multi-agent coordination, marketplace integrations, or external agent-to-agent trust boundaries.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).