What is passive-recon?

A collection of ways to gather information about a target without directly contacting its systems, using sources such as DNS, WHOIS, public certificates and internet routing records.

Use it for domain and subdomain discovery, certificate searches, technology identification, ownership checks and mapping IP ranges to organisations.

It helps map a target's domains, addresses and technologies while reducing the chance of creating logs or alerts on the target.

passive-recon — Skill for Claude Code by MingyiSecLab

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add MingyiSecLab/Mingyi-Atlas --skill passive-recon

Clone the repo

git clone --depth 1 https://github.com/MingyiSecLab/Mingyi-Atlas

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/passive-recon/github.svg)](https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/passive-recon)

Your own site

<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/passive-recon"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/passive-recon/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/passive-recon"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/passive-recon.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,121 The whole file, excluding the scripts and references it only reads on demand.

Security scan C 2 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00032	$0.03121
Opus 5	$0.00016	$0.01561
Sonnet 5	$0.00006	$0.00624
Haiku 4.5	$0.00003	$0.00312

Measured 9d ago against content hash 9c7b27071064, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade C, and why

passive-recon scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/parse_subdomains.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

curl -s "https://crt.sh/?q=%25.<TARGET>&output=json" | python3 -c "import sys,json; [print(x['name_value']) for x in json.load(sys.stdin)]" | sort -u

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s "https://crt.sh/?q=%25.<TARGET>&output=json" | python3 -c "import sys,json; [print(x['name_value']) for x in json.load(sys.stdin)]" | sort -u

src/skills/standard/recon/passive-recon/SKILL.md · 312 lines

How it starts

The opening of the file, as written. The whole thing — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Passive Reconnaissance Knowledge Base

Passive reconnaissance gathers intelligence without directly interacting with the target's systems. This leaves no logs, no alerts, and no fingerprints on the target. Always exhaust passive methods before transitioning to active techniques.

Quick Reference — Copy-Paste Commands

# Full passive workflow for <TARGET>
whois <TARGET>
dig <TARGET> ANY +noall +answer
subfinder -d <TARGET> -o subdomains.txt
amass enum -passive -d <TARGET> -o amass_subs.txt
curl -s "https://crt.sh/?q=%25.<TARGET>&output=json" | python3 -c "import sys,json; [print(x['name_value']) for x in json.load(sys.stdin)]" | sort -u
httpx -l subdomains.txt -sc -cl -ct -title -tech-detect -o httpx_<TARGET>.txt
curl -sI https://<TARGET>

1. WHOIS Intelligence

Domain WHOIS

whois example.com

Extract: Registrar, creation/expiration dates, nameservers, registrant organization, abuse contacts.

IP WHOIS (ASN Mapping)

whois -h whois.radb.net -- '-i origin AS12345'
whois <IP_ADDRESS>

Extract: ASN ownership, IP ranges allocated, network name, organization.

BGP/ASN Enumeration

# ASN lookup via Team Cymru
whois -h whois.cymru.com " -v <IP_ADDRESS>"

# All prefixes for an ASN
whois -h whois.radb.net -- '-i origin AS12345' | grep route

# Using amass for ASN intelligence
amass intel -asn <ASN_NUMBER>

Key Analysis Points

Registrar patterns: Same registrar across multiple domains may indicate shared ownership
Nameserver clustering: Shared NS records reveal infrastructure relationships
Registration dates: Recently registered domains may indicate campaign infrastructure
Privacy protection: WHOIS privacy services indicate security awareness
ASN ownership: Map all IP ranges belonging to the target organization

2. DNS Reconnaissance

Comprehensive Record Queries

# All record types
dig example.com ANY +noall +answer

# Specific records
dig example.com A +short
dig example.com AAAA +short
dig example.com MX +short
dig example.com NS +short
dig example.com TXT +short
dig example.com CNAME +short
dig example.com SOA +short

# Reverse DNS
dig -x <IP_ADDRESS> +short

Read the full file on GitHub · 312 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

9d ago First seen · 312 lines · 32 tokens per session scan C 9c7b27071064

Subscribe to this mod's changes

passive-recon is a skill published in the GitHub repository MingyiSecLab/Mingyi-Atlas (11 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 32 tokens to every session and 3,121 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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