Deep quality analysis of a dataset. Scores entries on diversity, realism, complexity, and training readiness.
AI agents call quality_score to retrieve information from OffensiveSET without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool reads and analyzes dataset properties (diversity, realism, complexity, training readiness) to produce quality metrics. It is a Read operation because it queries/evaluates data without side effects.
From the tool's definition Tool performs 'deep quality analysis' and 'scores entries' on existing datasets—a retrieval and evaluation operation with no modification, deletion, or execution of external systems.
Documented attack patterns abuse exactly the kind of access quality_score gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and OffensiveSET, and nothing reaches the server without passing your rules. This is the rule we recommend for quality_score:
{
"version": "1",
"default": "deny",
"tools": {
"quality_score": {}
}
}quality_score is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Deep quality analysis of a dataset. Scores entries on diversity, realism, complexity, and training readiness. It is categorised as a Read tool in the OffensiveSET MCP Server, which means it retrieves data without modifying state.
Register the OffensiveSET MCP server in PolicyLayer and add a rule for quality_score: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches OffensiveSET. Nothing to install.
quality_score is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the quality_score rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for quality_score. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
quality_score is provided by the OffensiveSET MCP server (pentesterflow/offensiveset). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 10 OffensiveSET tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
10 OffensiveSET tools catalogued and risk-classified — across an index of 42,500+ MCP servers.