target-recon

target-recon is a skill for Claude Code from ByamB4/find-cve-agent. It costs 31 tokens per session (1,182 once invoked), scanned A, original, Apache-2.0.

A method for finding npm, PyPI, and GitHub software packages that may be suitable for security review. npm and PyPI are package registries where developers publish JavaScript and Python code.

In plain words
What is it for?
Searching package registries and GitHub, checking usage and maintenance, and selecting manageable audit targets based on security-research criteria.
Why use it?
It narrows a large pool of packages to actively maintained projects that are widely used, handle untrusted input, and may still have overlooked security weaknesses.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the find-cve-agent plugin — 21 skills, 7 commands, 5 agents shipped together

Good fit Searching package registries and GitHub, checking usage and maintenance, and selecting manageable audit targets based on security-research criteria.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/byamb4/find-cve-agent/target-recon
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 ByamB4/find-cve-agent --skill target-recon
Clone the repo
git clone --depth 1 https://github.com/ByamB4/find-cve-agent

Made for: Claude Code.

Or install find-cve-agent, the plugin that ships this one along with the rest of its 21 skills, 7 commands, 5 agents.

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 target-recon

README.md
[![agentmods](https://agentmods.dev/badge/skills/byamb4/find-cve-agent/target-recon/github.svg)](https://agentmods.dev/skills/byamb4/find-cve-agent/target-recon)
Your own site
<a href="https://agentmods.dev/skills/byamb4/find-cve-agent/target-recon"><img src="https://agentmods.dev/badge/skills/byamb4/find-cve-agent/target-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.

agentmods 80×15 button for target-recon

Your own site · 80×15
<a href="https://agentmods.dev/skills/byamb4/find-cve-agent/target-recon"><img src="https://agentmods.dev/badge/skills/byamb4/find-cve-agent/target-recon.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,182 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.
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 $0.00031 $0.01182
Opus 5 $0.00015 $0.00591
Sonnet 5 $0.00006 $0.00236
Haiku 4.5 $0.00003 $0.00118

Measured 11d ago against content hash 1f063daec870, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

target-recon 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 11d 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.

skills/target-recon/SKILL.md · 140 lines

How it starts

The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Target Recon -- Finding High-Quality Audit Targets

When to Use

Starting a new research cycle. Need fresh targets with high CVE potential but low existing researcher attention.

Target Sweet Spot

The ideal target is a package that:

  • Is widely used (>100K weekly downloads on npm)
  • Handles untrusted input (parsing, validation, file processing)
  • Is small enough to audit in a day (< 10K lines of code)
  • Has few existing CVEs (< 5)
  • Is actively maintained (last commit within 6 months)
  • Has 500-15K GitHub stars

Avoid

  • Mega-packages (lodash, axios, moment, express, django, rails) -- too many researchers
  • Full frameworks (Next.js, Nuxt, Laravel) -- too large, too audited
  • >20K stars AND >10 prior CVEs -- over-audited territory
  • Abandoned packages (no commits in 2+ years) -- CVE may not be assigned
  • Alpha/beta packages -- maintainer may not issue CVE

Search Strategies

npm Search

# Search by category
npm search xml parser
npm search csv parse
npm search template engine
npm search file upload
npm search schema validator

# Check weekly downloads on npmjs.com
# Look for packages with 100K-10M weekly downloads

GitHub Search

# Search repos by language and star count
gh search repos "xml parser" --language javascript --stars 500..15000
gh search repos "yaml" --language python --stars 500..10000
gh search repos "template engine" --language javascript --stars 500..15000
gh search repos "archive extract" --language go --stars 500..10000

grep.app (Cross-Repo Code Search)

Search for vulnerable patterns across many repos:

https://grep.app/search?q=new%20Function&regexp=false&filter[lang][0]=JavaScript
https://grep.app/search?q=eval%28&regexp=false&filter[lang][0]=JavaScript

Libraries.io

Check dependency counts -- packages depended on by many other packages have higher impact.

Category-Based Targeting

Highest Yield Categories

Category Vulnerability Classes Example Packages
Parsing (XML/CSV/YAML) Entity expansion, ReDoS, clobbering fast-xml-parser, csv-parse, js-yaml
Validation/Schema Code injection, ReDoS, proto pollution ajv, joi, fastest-validator
Template Engines SSTI, code injection ejs, nunjucks, handlebars, pug
Archive/Compression Zip Slip, decompression bomb, path traversal adm-zip, decompress, fflate
File Handling Path traversal, symlink attacks express-fileupload, formidable
Deep Merge/Clone Proto pollution, recursion DoS deepmerge, rfdc, klona
Expression Evaluators Sandbox escape, code injection simpleeval, expr-eval, filtrex
HTTP Clients SSRF, header injection, auth leak got, superagent, needle
Serialization Clobbering, code injection, recursion flatted, superjson, msgpackr
URL/Path Utilities SSRF bypass, path traversal url-parse, normalize-url

Read the full file on GitHub · 140 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.

  1. 11d ago First seen · 140 lines · 31 tokens per session scan A 1f063daec870

Subscribe to this mod's changes

target-recon is a skill published in the GitHub repository ByamB4/find-cve-agent (48 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 31 tokens to every session and 1,182 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 2026-08-30.

Related

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