recon-for-sec

recon-for-sec is a skill for Claude Code, Codex from yaklang/hack-skills. It costs 41 tokens per session (312 once invoked), scanned A, original, MIT.

A starting guide for security testing an unfamiliar target. It explains how to confirm scope, discover assets, identify technologies, collect endpoints, and choose the next test.

In plain words
What is it for?
Use it to organize reconnaissance and route findings toward API, login, injection, or business-logic testing.
Why use it?
It gives a clear first route when you do not yet know what the system contains or which security checks matter most.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to organize reconnaissance and route findings toward API, login, injection, or business-logic testing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yaklang/hack-skills/recon-for-sec
About the project

HackSkills is an organized knowledge base of installable skills that gives AI agents practical security knowledge across areas such as web security, privilege escalation, reverse engineering, and digital forensics. It is intended for bug bounty work, penetration testing, CTF competitions, and authorized security research. The catalogue entries are the project's own master, category, and topic skills.

yaklang/hack-skills · 2,133 stars · on GitHub

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 yaklang/hack-skills --skill recon-for-sec
Clone the repo
git clone --depth 1 https://github.com/yaklang/hack-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 recon-for-sec

README.md
[![agentmods](https://agentmods.dev/badge/skills/yaklang/hack-skills/recon-for-sec/github.svg)](https://agentmods.dev/skills/yaklang/hack-skills/recon-for-sec)
Your own site
<a href="https://agentmods.dev/skills/yaklang/hack-skills/recon-for-sec"><img src="https://agentmods.dev/badge/skills/yaklang/hack-skills/recon-for-sec/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 recon-for-sec

Your own site · 80×15
<a href="https://agentmods.dev/skills/yaklang/hack-skills/recon-for-sec"><img src="https://agentmods.dev/badge/skills/yaklang/hack-skills/recon-for-sec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 312 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 22 Apr 2026
  • Snyk pass 22 Apr 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00041 $0.00312
Opus 5 $0.00020 $0.00156
Sonnet 5 $0.00008 $0.00062
Haiku 4.5 $0.00004 $0.00031

Measured 5d ago against content hash 6128ba665cb2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

recon-for-sec scanned grade A with 0 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 5d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

skills/recon-for-sec/SKILL.md · 29 lines

What it actually says

Recon and Methodology Router

This is the starting router for new targets and unknown attack surfaces.

When to Use

  • You just received a new target and do not yet know what to test first
  • You need to begin with asset discovery, tech fingerprinting, endpoint inventory, and test-route planning
  • You want to build follow-up testing on structured methodology instead of random payload enumeration

Skill Map

  1. First confirm in-scope assets and target type
  2. Then perform asset discovery, port/service identification, technology fingerprinting, and endpoint collection
  3. Route based on collected findings to api-sec, auth-sec, injection-checking, or business-logic-vuln
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. 5d ago First seen · 29 lines · 41 tokens per session scan A 6128ba665cb2

Subscribe to this mod's changes

recon-for-sec is a skill published in the GitHub repository yaklang/hack-skills (2,133 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 312 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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