dobenchmark — agentic threat model
The dobenchmark agent is a low-risk, highly deterministic utility for comparing PC hardware specifications against game requirements. It exhibits virtually no agentic properties, presenting minimal security risk beyond standard web application vulnerabilities and potential database inaccuracies.
OWASP AIVSS score rationale
| Autonomy of Action | 0.00 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.10 | |
| 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 — if an LLM is used to parse user queries or match specs, it faces minor prompt injection or misaligned output risks, but the core functionality is likely deterministic database lookups.
The agent relies on a static or regularly updated database of PC hardware specifications, game requirements, and benchmark data. Primary threats include data poisoning of the benchmark database or outdated hardware specs.
Not certain from the listing — there is no evidence of an agentic orchestration framework (like LangChain or AutoGPT). If one exists, threats are minimal due to the lack of write-access tools or complex memory.
Not certain from the listing — standard web hosting threats apply (e.g., DDoS, server misconfiguration). There is no indication of sandboxing or secure execution environments, which are likely unnecessary given the read-only nature.
Not certain from the listing — no evaluation, guardrails, or observability mechanisms are mentioned. Drift in hardware compatibility logic or benchmark data accuracy is the main operational risk.
Not certain from the listing — no authentication, authorization, or compliance frameworks (like GDPR or NIST) are mentioned, though the tool processes no personally identifiable information (PII).
The agent operates in isolation with no multi-agent or marketplace interactions. There is no risk of cascading failures or agent-to-agent trust abuse.
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 — every score is re-derived by the same automated method as an agent's public evidence changes.