NPM Sentinel MCP — agentic threat model
NPM Sentinel MCP acts as a read-only security utility providing package intelligence to other agents; its primary risk lies in downstream agents acting on poisoned or manipulated registry metadata to install malicious dependencies.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.60 | |
| Non-Determinism | 0.20 | |
| Opacity & Reflexivity | 0.20 |
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 specific foundation models used by the host agent interacting with this MCP tool are not defined, leaving potential model-level vulnerabilities unaddressed.
The tool ingests external data from the public npm registry and advisory databases. This introduces a risk of data poisoning, where malicious actors publish manipulated metadata or typosquatted packages to mislead the tool's analysis.
As an MCP tool, it integrates directly into agent frameworks. Vulnerabilities could arise from insecure tool integration, such as a host agent failing to sanitize package names before passing them to this tool, leading to command or query injection.
Not certain from the listing — The deployment environment (local MCP host, containerization, or cloud network policies) is not specified in the open-source directory listing.
Not certain from the listing — There is no mention of built-in logging, evaluation metrics, or guardrails to detect anomalous queries or drift in the tool's performance.
Not certain from the listing — No specific authentication, authorization, or compliance frameworks (such as NIST or ISO) are detailed for this utility.
Designed specifically to inform other agents' decisions. A compromised or poorly configured orchestrator agent could abuse this tool to scan for vulnerable packages to exploit, or conversely, make unsafe deployment decisions based on spoofed tool outputs.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).