target-recon
Skill2 starsChanged 2 months agoMITView on GitHub
Target discovery methodology for finding high-quality npm/PyPI/GitHub packages to audit for vulnerabilities, with evaluation criteria and search strategies.
In this repository255 other files it gives its agents.
- ad-acl-abuseSkill
- ad-adcs-access-and-relaySkill
- ad-adcs-persistenceSkill
- ad-adcs-template-abuseSkill
- ad-ad-discoverySkill
- ad-ad-persistenceSkill
- ad-auth-coercion-relaySkill
- ad-credential-dumpingSkill
- ad-gpo-abuseSkill
- ad-kerberos-delegationSkill
- ad-kerberos-roastingSkill
- ad-kerberos-ticket-forgingSkill
- ad-pass-the-hashSkill
- ad-sccm-exploitationSkill
- ad-trust-attacksSkill
- hunt-ntlm-infoSkill
- offensive-active-directorySkill
- hunt-llm-aiSkill
- hunt-rag-vectorSkill
- offensive-ai-securitySkill
- cloud-iam-deepSkill
- hunt-cloud-misconfigSkill
- hunt-k8sSkill
- m365-entra-attackSkill
- network-container-escapesSkill
- offensive-cloudSkill
- offensive-container-escapeSkill
- offensive-k8s-attacksSkill
- okta-attackSkill
- vmware-vcenter-attackSkill
- credential-password-sprayingSkill
- hunt-brute-forceSkill
- hunt-forgot-passwordSkill
- post-exploit-credential-recoverySkill
- meme-coin-auditSkill
- offensive-crypto-attacksSkill
- web3-auditSkill
- ctfSkill
- advisory-miningSkill
- auth-bypassSkill
- code-injection-codegenSkill
- command-injectionSkill
- cross-pollinationSkill
- cve-hunting-methodologySkill
- decompression-bombSkill
- entity-expansionSkill
- fp-checkSkill
- method-clobberingSkill
- path-traversalSkill
- prototype-pollutionSkill
- recursion-dosSkill
- redosSkill
- sandbox-escapeSkill
- web2-vuln-classesSkill
- evasion-av-edr-evasionSkill
- offensive-anti-forensicsSkill
- offensive-edr-evasionSkill
- offensive-keylogger-archSkill
- offensive-mitigationsSkill
- offensive-waf-bypassSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 65
Search for vulnerable patterns across many repos:
- Distinctive: line 72
Check dependency counts -- packages depended on by many other packages have higher impact.
- Distinctive: line 96
Check NVD: Search for existing CVEs
- Distinctive: line 97
Check GitHub Advisories: Look at security tab
- Distinctive: line 107
Write a brief for each approved target:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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 downloadsGitHub 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..10000grep.app (Cross-Repo Code Search)
Search for vulnerable patterns across many repos:
https://grep.app/search?q=new%20Function®exp=false&filter[lang][0]=JavaScript
https://grep.app/search?q=eval%28®exp=false&filter[lang][0]=JavaScriptLibraries.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 |
Evaluation Process
For each candidate:
- Check Registry: Is it already in REGISTRY.md?
- Check NVD: Search for existing CVEs
- Check GitHub Advisories: Look at security tab
- Read README: Does it warn about untrusted input?
- Check SECURITY.md: Does the project accept security reports?
- Read recent CHANGELOG: Any "security fix" entries? (incomplete patches are goldmines)
- Check HackerOne/bug bounty: Bonus, not required
- Estimate attack surface: What untrusted input does it process?
- Match to vuln classes: Which skills apply?
Brief Template
Write a brief for each approved target:
# Target Brief: [package-name]
- **GitHub**: [URL]
- **Stars**: [count]
- **Weekly Downloads**: [count]
- **Last Commit**: [date]
- **Language**: [JS/Python/Go/etc.]
## Attack Surface
- [What untrusted input does it process?]
## Existing CVEs
- [none / list with CVE IDs]
## Bug Bounty
- [yes/no + link]
## Top 3 Vectors
1. [Most likely vulnerability class + why]
2. [Second most likely]
3. [Third most likely]
## Why Promising
[1-2 sentences on why this target is worth investigating]References
- Parallel Scanning -- Batch evaluation methodology
- Search Queries -- Pre-built search queries by category
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

