deep-research (daymade) — agentic threat model
The deep-research agent poses a moderate-to-high risk due to its ability to write files directly to the host and execute web searches, exposing it to indirect prompt injection. However, its built-in source governance, citation registry, and mandatory counter-review passes provide strong logical mitigations against data poisoning and hallucinations.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.60 | |
| 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.
Not certain from the listing — the underlying LLM is not specified, but it is highly vulnerable to indirect prompt injection via untrusted web search results, which could manipulate the research output or hijack the file-writing tool.
The agent utilizes a citation registry, source-type governance, and freshness checks to manage its data operations. The primary threat is data poisoning of external web sources retrieved during runtime, which could compromise report integrity.
The framework orchestrates web searches, counter-reviews, and file outputs on the host. Threats include insecure tool integration where malicious inputs could exploit the file-writing capability to overwrite critical host files.
Not certain from the listing — the hosting environment is described generally as 'on the host' without specifying sandboxing, containerization, or privilege isolation, posing a risk of host compromise if the agent is exploited.
The agent features strong built-in observability and evaluation controls, specifically 'mandatory counter-review' and 'freshness (AS_OF) checks' to detect outdated information and logical inconsistencies before outputting reports.
Not certain from the listing — there are no explicit details regarding authentication, authorization, or compliance frameworks (such as NIST or ISO) for this open-source community skill.
Not certain from the listing — although labeled as a 'Community Agent Skill', there is no explicit mention of multi-agent coordination or ecosystem-level trust boundaries.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).