performing-osint-recon-on-simulated-target

performing-osint-recon-on-simulated-target is a skill for Claude Code, Codex from withcrux/agentHack-skills. It costs 64 tokens per session (1,513 once invoked), scanned A, original, no licence file.

A procedure for gathering public information about a simulated organization in an authorized lab. OSINT means researching publicly available information, while DNS and certificate transparency records describe domains and issued website certificates.

In plain words
What is it for?
DNS checks, certificate-record searches, public-source research, and Google dorks against the simulated target.
Why use it?
It provides a defined reconnaissance process without targeting real people or organizations.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit DNS checks, certificate-record searches, public-source research, and Google dorks against the simulated target.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/withcrux/agenthack-skills/performing-osint-recon-on-simulated-target
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 withcrux/agentHack-skills --skill performing-osint-recon-on-simulated-target
Clone the repo
git clone --depth 1 https://github.com/withcrux/agentHack-skills

Made for: Claude Code, Codex.

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.

agentmods badge for performing-osint-recon-on-simulated-target

README.md
[![agentmods](https://agentmods.dev/badge/skills/withcrux/agenthack-skills/performing-osint-recon-on-simulated-target/github.svg)](https://agentmods.dev/skills/withcrux/agenthack-skills/performing-osint-recon-on-simulated-target)
Your own site
<a href="https://agentmods.dev/skills/withcrux/agenthack-skills/performing-osint-recon-on-simulated-target"><img src="https://agentmods.dev/badge/skills/withcrux/agenthack-skills/performing-osint-recon-on-simulated-target/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.

agentmods 80×15 button for performing-osint-recon-on-simulated-target

Your own site · 80×15
<a href="https://agentmods.dev/skills/withcrux/agenthack-skills/performing-osint-recon-on-simulated-target"><img src="https://agentmods.dev/badge/skills/withcrux/agenthack-skills/performing-osint-recon-on-simulated-target.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,513 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00064 $0.01513
Opus 5 $0.00032 $0.00757
Sonnet 5 $0.00013 $0.00303
Haiku 4.5 $0.00006 $0.00151

Measured 12d ago against content hash cb4030dbe9f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

performing-osint-recon-on-simulated-target scanned grade A with 1 finding 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 12d ago.

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.

Makes network callslowCapability

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

curl http://crt-sim.lab/acme-corp.lab | jq '.[].name_value' | sort -u
skills/performing-osint-recon-on-simulated-target/SKILL.md · 162 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

What ships with it

1 file 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.

  1. 12d ago First seen · 162 lines · 64 tokens per session scan A cb4030dbe9f0

Subscribe to this mod's changes

performing-osint-recon-on-simulated-target is a skill published in the GitHub repository withcrux/agentHack-skills (5 stars, last pushed 5mo ago), with no licence file. It adds 64 tokens to every session and 1,513 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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