MindSearch — agentic threat model
MindSearch is an open-source multi-agent web search framework whose primary risk lies in indirect prompt injection from untrusted web content retrieved during searches, which could compromise the multi-agent planning and execution flow.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.90 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.60 |
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 foundation LLMs to plan and execute search queries. Highly vulnerable to indirect prompt injection and adversarial manipulation via the text retrieved from external web pages.
Ingests dynamic, untrusted web data in real-time. Lacks inherent data lineage or verification, making it susceptible to data poisoning from malicious websites designed to hijack the LLM's context.
As a multi-agent framework, it orchestrates planning and tool calling (search APIs, web scrapers). Vulnerabilities include insecure tool execution, SSRF via search queries, and memory poisoning during a search session.
Not certain from the listing — as an open-source framework, deployment infrastructure depends entirely on the user's setup, but running web scrapers/browsers requires robust sandboxing to prevent SSRF or local file inclusion.
Not certain from the listing — the public directory does not specify built-in evaluation, logging, or guardrail mechanisms for the search outputs.
Not certain from the listing — no explicit security controls, compliance certifications, or access control policies are mentioned in the brief description.
Employs a multi-agent architecture where agents coordinate to solve search tasks. A compromise in one agent (e.g., the web-scraping agent via injection) can easily propagate to the planner agent, leading to cascading failures.
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.