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echelongraph

EchelonGraph MCP Server

Official
by echelongraph

cve_exposure

Look up the internet-exposure footprint for a CVE: count internet-facing services running a version mapped to it, with country, product, and ransomware context.

Instructions

Internet-exposure footprint for one CVE from EchelonGraph's KEV-exposure radar: how many internet-facing services (distinct ip:port, returned as exposed_hosts; a machine answering on two ports counts twice) the radar has on record running a version its CVE matcher maps to this CVE, with a country/product breakdown and a ransomware flag. Aggregate and host-redacted; free and keyless. Method: exposure counts are derived from Shodan data. Shodan data is owned by Shodan, which holds its copyright (© Shodan). Every 12 h, when Shodan query credits allow, the radar runs one Shodan query per tracked product, reads up to 100 ip:port services per query, and keeps a service when its banner version matches a CISA-KEV or high-EPSS CVE; a service not seen on its port for 21 days is dropped. last_seen is when a service was last seen listening on its port, not when its vulnerable version was last confirmed: between searches a re-check that finds the port still listed refreshes it without re-reading the banner, so a patched service can stay counted while its port stays open. A count is therefore a banner-version inference over a sample, not an exploit test and not an internet-wide census. The radar only looks for its tracked set of CVEs: for a CVE outside that set the result says NOT ASSESSED, and its 0 is not a measurement.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cve_idYesa CVE ID, e.g. CVE-2023-44487

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.3

TDQS

A4.3/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and does so richly: it discloses the data source (Shodan), the 12h refresh cadence and credit limits, the 21-day staleness drop, the crucial caveat that last_seen is port-liveness rather than vulnerability confirmation, that counts are banner-version inferences over a sample rather than exploit tests or a census, and that it is aggregate, host-redacted, free and keyless.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose is front-loaded in the first clause, which is good, but the single dense paragraph runs long and includes material of questionable necessity (the Shodan copyright/ownership aside) alongside genuinely valuable caveats. Each caveat earns its place; the legal aside and some redundancy do not.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description must describe the return shape, and it does: exposed_hosts count with the double-counting rule, country/product breakdown, and a ransomware flag. Combined with the scope and methodology caveats, an agent has everything needed to interpret the result correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single cve_id parameter is fully documented in the schema (100% coverage), so the schema does the heavy lifting. The description adds meaning about which CVE values are actually assessed (tracked set vs NOT ASSESSED), but no syntax or format detail beyond the schema's own example.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: 'internet-exposure footprint for one CVE', and immediately defines the unit (distinct ip:port, exposed_hosts) and the scoping to a single CVE, which cleanly separates it from aggregate siblings like exposure_radar and lookup siblings like get_cve. An agent knows exactly what this returns without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context for when the tool is informative versus not: it only assesses a tracked set of CVEs, and for anything outside that set the result says NOT ASSESSED and its 0 is not a measurement. It does not, however, explicitly route the agent to a named alternative (e.g., exposure_radar or cve_summary) for cases where a per-CVE view is the wrong choice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.