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aws-audit-mcp

by OmniNomadLLC

audit_world_open_security_groups

Read-only

Audits EC2 security groups in a region and flags ingress rules open to 0.0.0.0/0 or ::/0, identifying sensitive ports as high severity and returning normalized findings.

Instructions

Audit EC2 security groups for ingress rules open to the world.

Scans every security group in the region (AWS_REGION or us-east-1 when the region argument is omitted) and flags each ingress rule whose source is 0.0.0.0/0 or ::/0. Rules allowing all traffic (protocol -1) or covering a sensitive port (SSH 22, RDP 3389, MySQL 3306, PostgreSQL 5432, Redis 6379, Elasticsearch 9200, MongoDB 27017) are HIGH; any other world-open port (for example 80 or 443) is MEDIUM.

Returns a dict {check, ok, findings, scanned} where ok is true only when no findings were produced, findings is a list of normalized finding dicts (check, severity, title, resource, detail with protocol, from_port, to_port, cidrs, group_name), and scanned is the number of security groups examined.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionNo
Behavior5/5

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

The description goes far beyond the annotations: it explains the default region resolution from AWS_REGION, the exact CIDRs considered world-open, the severity classification for sensitive ports, and the full return dict shape with each key's meaning. This provides rich operational context that annotations alone do not convey.

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

Conciseness5/5

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

The purpose is front-loaded and each sentence adds operational detail. The layout clearly separates scope, severity criteria, and return value. It is long but every part is necessary for correct invocation and interpretation.

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 fully documents the return value including the fields in each finding. It also covers region behavior, scanning scope, and severity rules. Nothing essential is missing for an agent to select and invoke this tool.

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

Parameters5/5

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

The only parameter, region, has no schema description, but the description fully compensates: it explains that region defaults to null, falls back to AWS_REGION, and then to us-east-1. This is exactly the semantic detail an agent needs to call the tool correctly.

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?

The description states a specific verb ('Audit'), a specific resource ('EC2 security groups'), and a precise criterion (ingress rules open to the world). This clearly distinguishes it from sibling audit tools like audit_public_buckets or audit_ebs_exposure.

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?

The description makes it clear when this tool is relevant: when you need to audit security groups for world-open ingress. It also explains region selection behavior. It does not explicitly name alternative tools or exclusions, but the purpose is so specific that an agent can infer appropriate use.

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

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