Playwright MCP — agentic threat model
Playwright MCP presents a high agentic risk profile because it grants LLMs direct, active browser automation capabilities (clicking, typing, navigating), making it a prime target for indirect prompt injection and unauthorized tool execution if deployed without strict sandboxing.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.90 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.30 |
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 — Playwright MCP is an MCP server rather than a foundation model. However, the orchestrating LLM is highly vulnerable to indirect prompt injection when processing untrusted web page content retrieved by this tool.
Not certain from the listing — The tool processes live web page data (accessibility trees, DOM structure) on the fly rather than managing a vector database. The primary threat is ingestion of malicious or poisoned web data.
Exposes powerful browser automation tools (click, type, navigate, wait) via the Model Context Protocol. This creates a severe risk of tool misuse, where an LLM is manipulated into performing unintended actions on live websites (e.g., submitting forms, triggering transactions, or exfiltrating data).
Not certain from the listing — The deployment environment is self-hosted by the user. If the browser instance is not strictly sandboxed, a compromised session could allow lateral movement, local network scanning (SSRF), or host compromise.
Not certain from the listing — There are no details regarding built-in logging, execution guardrails, or anomaly detection to monitor the browser actions taken by the LLM.
Not certain from the listing — No authentication, authorization, or policy enforcement mechanisms (such as domain whitelisting or read-only modes) are described in the listing.
Designed to integrate directly into agentic ecosystems via MCP. A compromised or rogue agent utilizing this tool could cause cascading failures by executing automated attacks or spamming external web services.
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.